Free scan, under 30 seconds: your validated Face Score — a percentile checked against 5,500 human-rated faces — plus 3 of your 17 geometry measurements. Private, no signup.
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What happens next
Free scan — your validated Face Score, 3 of your 17 measurements (opening on your standout — strongest or weakest), and a retake coach if the photo is underselling you. Up to 5 free scans a day.
Full report — all 17 measurements, your weakest metric with fixes + your 30-day plan is the paid unlock: $14.99 + 3 days of Pro included. We show the price here so you never meet it for the first time at a paywall. See a sample
Private — Photos are processed in memory and deleted instantly — never stored, never used for training.
The RealSmile looksmaxxing test measures 17 facial-geometry metrics — symmetry, canthal tilt, FWHR, gonial angle, midface ratio, and 12 more — from a single selfie as a Measurement Map of your features (real readings, not an attractiveness rating; Grammer & Thornhill 1994; Farkas 1994; Carré & McCormick 2008), and returns your validated Face Score free — a percentile cross-validated at r ≈ 0.8 against 5,500 human-rated faces. Photos are processed in memory and deleted instantly — never stored, never used for training.
Looksmaxxing is the systematic, evidence-based improvement of physical appearance by optimizing the three structural predictors of facial attractiveness supported by meta-analysis, symmetry, averageness, and sexual dimorphism (Rhodes, 2006), plus controllable presentation factors such as grooming, skincare, fitness, posture, and photo technique.
The term originated in online self-improvement communities and has gone mainstream on TikTok, Reddit, and YouTube as people realize that small, consistent changes to grooming, skincare, fitness, and photo presentation have outsized effects on first impressions. First impressions of attractiveness, trustworthiness, and competence form from a face in roughly 100 milliseconds (Willis & Todorov, 2006), and a lot of it is under your control.
The looksmaxxing approach is divided into two categories. Softmaxxing includes non-invasive improvements like skincare routines, hairstyle optimization, eyebrow grooming, fitness, posture correction, and learning to photograph well. Hardmaxxing involves surgical or medical procedures. This looksmaxxing test — often shortened to the looksmax test or spelled the looksmaxing test — focuses entirely on softmaxxing, actionable improvements anyone can make.
The goal of this test isn't to rate your attractiveness in any absolute sense. Instead, it gives you objective facial measurements compared to population averages, then tells you what you can actually improve through grooming, fitness, and photo technique.
The only validated looksmax test
Most looksmaxxing tests are golden-ratio "beauty calculators" that never check their looksmaxxing rating against how real people actually rate faces. RealSmile is the only one that does. Your Face Score — free with every scan — is a validated percentile: it agrees with averaged human ratings at r ≈ 0.8, cross-validated against 5,500 human-rated faces in the SCUT-FBP5500 academic benchmark (60 ratings per face). See the full validation →
This is the question that actually matters when you take a looksmax test, and it deserves a real answer rather than a marketing one. Most looksmaxxing calculators are golden-ratio tools: they compare your proportions to a fixed template and never check whether that template matches how real people rate real faces. On the standard academic benchmark, that golden-ratio approach reaches only about r ≈ 0.55–0.65 correlation with human ratings — which is why a "beauty calculator" can hand you a harsh looksmaxxing rating no actual person would agree with.
RealSmile's Face Score is measured differently. We ran our production pipeline against SCUT-FBP5500 — 5,500 face photos, each independently rated for attractiveness by 60 people — using 5-fold cross-validation, so every number is scored on faces the model never saw while fitting. The Face Score reaches a cross-validated r ≈ 0.8 against the averaged human ratings. For reference, the best published deep-learning models on this benchmark reach r ≈ 0.85–0.90.
We hold the geometry to the same test. Our original 17-metric blend failed it — no positive correlation with human ratings (r ≈ −0.33, slightly anti-correlated) — so we published that finding and stopped presenting the 17 metrics as an attractiveness number. That is why the geometry is a Measurement Map, not a looksmax verdict. To our knowledge, no other looksmaxxing test publishes any validation of its scoring against human ratings at all.
Methodology & editorial
Every scan uses 68-point iBUG 300-W facial-landmark detection to place the geometry, then the Face Score model estimates your percentile. Photos are processed in memory and deleted instantly — never stored, never used for training. This page is maintained by Randy, founder of RealSmile; the full study list and validation write-up are public on the research base, and the citation chain is checkable there.
A looksmax score is a position, not a verdict. Your scan gives you two different outputs, and reading them correctly is the whole point:
A validated percentile that tells you where a still photo of your face lands against a large population. This is the output built to answer "how do I rate", because it is cross-validated at r ≈ 0.8 against how real people rate faces. A percentile is a position, not a judgment of your worth — and most people who take a looksmaxxing test land closer to the middle than they fear.
Canthal tilt, FWHR, symmetry, jawline angle, midface ratio and 12 more: a map of how each feature measures against population norms. It is not an attractiveness rating. We tested blending the 17 metrics into a single number and it did not predict how people rate a face (r ≈ −0.33), so we present it as a map. Use it to find the one or two metrics scoring below their ideal range — the specific, usually softmaxxable things worth your attention. What each of the 17 measurements means →
The honest read for almost everyone who takes this looksmax test: your looks are probably more average — in the statistical, middle-of-the-distribution sense — than your inner critic claims, plus one or two specific things you have been over-weighting. That is a far more useful, and more hopeful, answer than a single looksmaxxing rating out of 100.
When people take a looksmax test, half of them want a validated number and half want real people to weigh in. RealSmile is the only tool that gives you both on the same photo. Your Face Score is the validated AI read (r ≈ 0.8 vs human ratings); your Human Score is the average of 10+ real people rating your photo — free, numbers only, moderated, and deletable anytime.
Put them head-to-head and the comparison is genuinely useful. If the AI and the crowd both land you in the same band, that is a strong, stable signal about how a still photo of you reads. If they diverge, it usually points at something specific — an expression or lighting quirk the model reads differently than a person does — worth fixing before you use the photo for dating apps or LinkedIn. No golden-ratio looksmaxxing calculator can offer this, because none of them have a validated number or a real crowd behind it.
Searchers often arrive with looksmax community labels (LTN/MTN/HTN/Chad). Below is how those labels translate to RealSmile's 0-100 score — described honestly, not as a hierarchy.
Low geometry-conformance read on first-photo metrics
Usually 1-2 photo/lighting variables depressing the read; not a structural ceiling.
Median band — most uploaders sit here
Closest band to population mean; small situational lifts (lighting, posture) shift you up notably.
Upper-quartile read
Photo polish + outfit/setting consistency tends to be the lever, not face changes.
Top-decile composite read
Diminishing returns on face changes; situational presentation is the multiplier.
Top ~2-5% composite read on RealSmile sample
Sample-level ceiling, not a clinical ranking; outliers in this band are rare.
These labels are colloquial — they describe relative position within the RealSmile sample, not clinical attractiveness rankings, and have not been validated against peer-reviewed research. We surface them only as a vocabulary bridge for users who arrived via the looksmax community.
Illustrative output. Numbers below are a sample profile, not your data.
Sample profile
Sample score 71/100
Percentile
Top 28%
[>] Strong. Genuine cheek lift. Avoid forced grin photos.
[>] Above population avg (~85%). No action needed.
[>] Mid-thirds 2pt longer than ideal. Hairstyle can mask.
[>] Gonial angle soft. Lower body fat 3-5% to reveal definition.
[>] Texture mid-range. SPF + retinol = visible lift in 6-8 wks.
Weakest axis
Jawline
Highest ROI
Body fat
Est. lift
+11 pts
Sample shown for illustration. Your scan returns your validated Face Score percentile plus the 17-metric Measurement Map, scored from your photo's landmark geometry.
Compares left and right sides of your face across jawline, eyes, brows, and mouth. Population average is ~85%. Highly symmetric faces score 92%+.
The angle of your eye corners. Positive (upward) tilt at the outer corners creates the "hunter eyes" look associated with alertness and attractiveness. Ideal canthal tilt: 4-7°.
How wide your face is relative to midface height. FWHR ratios of 1.8-2.0 are linked with perceived dominance and attractiveness in peer-reviewed research.
Whether your forehead, midface, and lower face are proportionally equal. The classical ideal is equal thirds (33/33/33).
The distance between your eyes relative to eye width. The classical ideal is exactly one eye-width between the eyes (ratio of 1.0).
The angle of your jaw from chin to jaw corner. Our jaw-slope measure typically reads 45-55° on defined jaws (this is our landmark measure, not the surgical ‘gonial angle’). One of the most important looksmaxxing metrics for men.
Nose width as a percentage of total face width. The classical ideal is 22-26%.
The balance between upper and lower lip fullness. A slightly fuller lower lip (ratio of 0.5-0.8) is considered ideal.
The compactness of your midface region. A shorter midface (0.42-0.48) is associated with youthful, attractive proportions.
Eye width-to-height ratio. More elongated, narrow eyes (2.8-3.5) are the "hunter eye" shape. This is one of the most popular metrics in looksmaxxing communities.
Most facial metrics are influenced by both genetics and controllable factors. Here are the highest-ROI softmaxxing improvements:
Getting to 12-15% body fat (men) or 18-22% (women) reveals jawline definition, cheekbone structure, and improves nearly every facial metric. This is the single most impactful softmaxxing change.
The highest-ROI grooming change. Clean, shaped brows frame the eye area, can shift perceived canthal tilt, and improve facial symmetry in photos. Directly impacts 3 metrics.
A simple routine (cleanser, moisturizer, SPF) improves skin texture and clarity, which affects how every feature photographs. Visible results in 4-8 weeks.
Camera angle, lighting, and expression have massive effects. Natural light from the side, camera at eye level, and a genuine smile can shift your perceived looksmax score substantially.
The right hairstyle can rebalance facial proportions — adding width to a narrow face (improving FWHR), covering a high forehead, or framing the eye area differently.
Forward head posture compresses the jawline and creates a double chin effect. Good posture lengthens the neck and defines the jaw angle.
More than one scan
One tap creates your free account right after your scan — nothing extra to fill in.
Jawline Test
Gonial angle + definition score
Canthal Tilt Test
Eye angle measurement in degrees
Hunter Eyes Test
Eye shape + hooding + tilt analysis
FWHR Calculator
Facial width-to-height ratio
Masculinity Test
5 masculinity markers scored
Symmetry Test
Detailed bilateral symmetry analysis
Am I Ugly Test
Honest AI face breakdown
All 8 Tests
Full free looksmax scorecard
Face Score
AI expression + smile analysis
Attractiveness Test
How attractive am I?
Free · Under 30 seconds · No signup
17 facial metrics. AI-measured. Instant results.
Private — never stored · Deleted instantly
No signup · Free to try · Full report $14.99 one-time
Improve your results
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Results in 2-4 weeksCurated based on facial analysis data. No photos collected. Affiliate links — we earn a small commission at no extra cost to you.
See all →Facial analysis tools like this one are built on decades of peer-reviewed research in facial geometry, evolutionary psychology, and computer vision. The metrics measured here aren't arbitrary — each one has an established research foundation linking it to perceived attractiveness, health signaling, or social dominance perception.
Facial Width-to-Height Ratio (FWHR) was identified as a predictor of perceived dominance in a 2008 study by Carré and McCormick in the Proceedings of the Royal Society B. Higher FWHR correlates with perceived assertiveness and leadership presence. Separately, a 2010 study found FWHR also predicts financial performance in CEOs.
Canthal tilt — the angle of the outer corners of the eyes relative to the inner corners — emerged as a significant attractiveness predictor in studies analyzing what distinguishes conventionally attractive faces. A positive canthal tilt (outer corners higher than inner) correlates strongly with ratings of attractiveness in both men and women.
Facial symmetry has been linked to developmental stability and genetic health since the 1990s. Research by Randy Thornhill and Steven Gangestad found that more symmetrical individuals are rated as more attractive and report more dating and relationship success on average. The effect is real but modest — asymmetry alone doesn't determine attractiveness.
Jawline definition (measured via jaw angle and chin projection) signals hormonal health — specifically testosterone exposure. A well-defined jaw is consistently rated as masculine and attractive in male faces, and as strong and confident in female faces. This measurement differs from most online “jaw tests” in that it uses actual geometric angles rather than subjective ratings.
Left-to-right balance across all major features. Measured as a percentage deviation — 100% is perfect symmetry, which no face actually achieves.
The angle of the outer eye corners relative to the inner corners. Positive = outer higher than inner (associated with attractiveness). Measured in degrees.
Facial width-to-height ratio. Width measured at cheekbones, height from upper lip to brow. Higher values correlate with perceived dominance.
The angle of the jaw from ear to chin. A sharper angle indicates a more defined jawline; a wider angle indicates a softer, rounder jaw shape.
Composite score based on canthal tilt, eyelid exposure (how much of the iris is visible), and brow position. High scores = hooded, almond-shaped eyes.
Division of the face into three equal horizontal thirds (forehead, midface, lower face). Ideal balance is roughly 33%/33%/33%.
The height of the midface (brow to upper lip) relative to total face height. Shorter midfaces are generally rated as more attractive.
Distance between eyes as a fraction of face width. Ideal eye spacing follows the golden ratio principle — each gap equals one eye width.
Nose width relative to face width and nose length relative to midface height. Both contribute to perceived facial harmony.
Upper-to-lower lip thickness ratio. Most attractiveness research points to a ratio of approximately 1:1.6, with a fuller lower lip.
The curvature ratio of the brow relative to its width. A moderate arch is associated with an alert, expressive appearance. Measured as a curvature ratio.
Length of the philtrum (the groove between nose and upper lip) as a fraction of the lower face. Shorter philtrums are generally rated as more attractive.
Chin height as a fraction of the lower third of the face. Balanced chin proportion contributes to overall facial harmony and profile aesthetics.
The vertical distance between the brow and the upper eyelid, measured as a ratio. Closer brow-eye distance is associated with a more intense, defined eye area.
Ratio of jaw width to chin width. A higher taper indicates a more V-shaped jawline — tapered toward the chin — which is a common looksmaxxing goal.
An experimental phi-proportion measure comparing multiple facial proportions against the golden ratio (1.618). We’re recalibrating this one — treat it as directional.
How symmetrically the eye sockets are angled — comparing the orbital tilt of the left and right eye. High asymmetry here is one of the most noticeable facial imbalances.
Facial geometry is one component of appearance — and appearance is one component of attractiveness. This test measures structural facial metrics objectively. It does not measure expression quality (see our Smile Analyzer), skin quality, grooming, style, body language, voice, personality, or any of the dozens of other factors that determine how attractive someone actually is in person or in photos.
Many people with “below average” scores on individual metrics are considered highly attractive by others. Many people with high scores are not. The research correlations are real but modest — treat this as useful self-knowledge, not a verdict.
The most actionable insights from this test are usually the ones that point to improvable factors: expression quality, photo lighting, posture, and — for longer-term goals — areas where lifestyle changes like training, sleep, and skincare can make meaningful differences.
For readers who want to dig deeper into the proportion side of the report, our 17-metric facial proportion methodology walks through how each ratio is computed, and our research-backed golden-ratio symmetry analysis covers what phi actually predicts in the empirical literature. If you want a tool-comparison view of where this engine sits versus other consumer raters, our AI face rating tool deep-dive shows the reproducibility checks separating real measurement from randomized entertainment. And if you want a plain-English glossary, what each of the 17 measurements means explains, metric by metric, what each number reads from your photo, what it isn’t, and whether you can change it.