Women · Free AI Face Score

Female Attractiveness Test (2026)

If you have ever wondered whether the photo you keep retaking is the right one, this is the answer in numbers. The female attractiveness test scores all 17 metrics with weighting that recognises what perception research actually finds matters in women's photos: facial symmetry, eye warmth, smile genuineness, midface harmony, and a soft-light read that doesn't flatten dimension. No upload. No signup. The score is yours in under ten seconds.

38,000+ faces analyzed · 100% private · Photos never uploaded

The 17 metrics — what matters most for women

The same 17-metric scoring engine runs across every attractiveness-test variant on RealSmile — symmetry, FWHR, midface ratio, canthal tilt, jawline definition, eye spacing, philtrum-to-chin ratio, lip-fullness, smile authenticity, eye warmth, skin quality, and more. The audience-specific weighting below explains which of those metrics carry extra weight for women and why.

Facial Symmetry

Across the meta-analysis literature (Rhodes 2006, Little et al. 2011) symmetry loads heaviest on female-face attractiveness ratings — even more than for male faces. The metric is sensitive to camera tilt; a level head-on shot scores up to 9 points higher than a 15° head-tilted shot.

Eye Warmth (Duchenne crinkle)

Eye-area warmth — visible orbicularis oculi engagement — is the single strongest predictor of perceived approachability in female portraits. The metric is suppressed by flat fluorescent lighting and lifted by soft window light or golden-hour outdoor light.

Midface Ratio

Midface ratio (cheek-width / jaw-width) in the 1.05–1.18 band tracks the youth-marker subset of female-attractiveness scoring. The metric is camera-angle-sensitive — eye-level camera photographs the ratio truer than below-chin angles.

Lip Fullness Ratio

Lip-fullness ratio loads positively on female-face attractiveness in research from Bisson & Grobbelaar (2004). The metric reads truest with neutral lipstick or lip balm; matte-flat lipstick can suppress the reading by an average of 4 points.

Smile Authenticity

Female-photo scoring weights Duchenne markers (AU6 cheek raise + AU12 lip-corner pull) heavily because forced/closed-mouth smiles read as guarded in first-impression studies. A genuine smile lift is the single biggest score change we see for women across audit retakes.

Skin Quality (texture + tone uniformity)

For women, skin-quality readings explain 10–14% of score variance in the audit dataset — more than for men. Soft, indirect lighting and avoidance of harsh ring-light shadowing are the simplest improvements.

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What each score band means for women

The audit returns a 0–100 score broken into four bands. Bands mean different things depending on audience — here is what each tier typically reflects when the photo is scored for women.

Top band85–100

Top-band female photos compound symmetry + soft light + a real smile. This is your dating-app lead, your LinkedIn headshot, your professional bio shot. Improvement plans focus on photo selection across your existing camera roll, not feature work.

High band70–84

High-band female photos usually have one drag — most often a forced smile, harsh top-down lighting that hollows the eyes, or a head-tilt angle suppressing the symmetry reading. A retake at eye level with window light typically lifts the score 7–11 points.

Mid band50–69

Mid-band female photos trace to lighting and expression more than to features. Flat overhead light, a closed-mouth smile, or a 15°+ head tilt are the three most common causes. Fix the lighting first — it's the one with the biggest single-change lift.

Low band0–49

Low-band female photos are almost never about the face. The audit retake plan focuses on lighting (window light at 45°), expression (genuine smile), and angle (camera at eye level). Most low-band female photos move 18+ points on a single retake without any feature change.

Female attractiveness test — FAQ

What is a good attractiveness score for women?+
For female photos, scores above 70 routinely outperform on dating apps in our audit dataset. Above 82 is top-decile. Below 55 is almost always a lighting or expression issue, not a feature issue — most photos in the 35–55 band lift to 65+ on a single retake.
Does the female attractiveness test favour a particular look?+
No. The metrics are landmark-derived ratios — eye spacing, midface ratio, lip-fullness ratio, symmetry — normalized to your own interpupillary distance. The model has no aesthetic template; the same face scores the same regardless of skin tone or ethnicity. Weighting comes from perception research, not from celebrity references.
How can I improve my female attractiveness score?+
Four highest-leverage levers: (1) soft window light at 45°, never overhead fluorescents; (2) genuine Duchenne smile — eye crinkle plus cheek raise; (3) camera at eye level, head straight (not tilted); (4) neutral makeup, no matte-flat lipstick that hides lip-fullness reading. Most users gain 12–22 points from these alone.
Is the photo upload private?+
Yes. The female attractiveness test runs entirely in your browser via TensorFlow.js. No image bytes leave your device — open your network tab during the scan and you will see no upload request. This is structurally different from Photofeeler, QOVES, Aurale, and Umax, all of which upload your photo to their server.
How is this different from "am I pretty" tests?+
"Am I pretty" sites typically upload photos, show ads, and give vague feedback. The female attractiveness test is 100% private (nothing uploaded), gives specific actionable feedback per metric, and scores expression quality — what you can change — alongside features. The free tier is genuinely free; the audit ladder is one-time, not subscription.

Related tests & tools

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See which of your photos actually wins.

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Other attractiveness-test variants