Every peer-reviewed study RealSmile cites, mapped to the page that uses it. If a claim on RealSmile is not supported by a study in this list, treat it as opinion, not evidence.
Maintained by Randy, founder of RealSmile. Last verified 2026-05-23.
Willis & Todorov (2006) · Psychological Science
Observers form attractiveness, trustworthiness, competence, and aggressiveness judgments from a face in roughly 100 milliseconds. Longer exposures increase confidence in the initial verdict rather than changing it.
Todorov & Porter (2014) · Psychological Science
Face impressions are formed in as little as 33 milliseconds and are stable across longer exposures. Lighting and pose changes shift the impression by more than the underlying structure does.
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Penton-Voak et al. (2001) · Proceedings of the Royal Society B
Jawline definition and lower-face masculinity are reliable predictors of perceived attractiveness in male faces. The effect is independent of symmetry.
Rhodes (2006) · Annual Review of Psychology
Meta-analysis identifies three structural predictors of facial attractiveness: symmetry, averageness, and sexual dimorphism. Averageness is often the largest single contributor.
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Grammer & Thornhill (1994) · Journal of Comparative Psychology
Bilateral facial symmetry is rated as more attractive across cultures and is associated with perceived dominance via the facial width-to-height ratio.
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Ekman & Friesen (1978) · Consulting Psychologists Press
A Duchenne (genuine) smile combines Action Unit 6, orbicularis oculi engagement around the eye, with Action Unit 12, zygomatic major lip-corner pull. Posed smiles use only AU12.
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Hamermesh & Biddle (1994) · American Economic Review
Workers rated above average in physical appearance earn roughly 5 percent more, and those rated below average earn roughly 9 percent less, controlling for education and experience.
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Langlois & Roggman (1990) · Psychological Science
Composite (averaged) faces are consistently rated more attractive than the individual faces from which they were built. Averageness, not rarity, drives attractiveness.
Carre & McCormick (2008) · Proceedings of the Royal Society B
Facial width-to-height ratio above 2.0 is associated with perceived dominance and aggressive behavior in men.
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Todorov & Olivola (2008) · Scientific American Mind
Snap judgments of competence from a single face photo predict real political election outcomes above chance. The effect generalizes to hiring and partner-selection contexts.
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Geniole et al. (2015) · PLOS ONE
Meta-analysis confirms FWHR signals perceived threat and dominance, but the effect on perceived attractiveness is small and context-dependent.
Zaidel & Cohen (2005) · International Journal of Neuroscience
Lighting direction shifts perceived facial symmetry by up to 23 percent independent of the underlying structure.
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Farkas (1994) · Raven Press, New York
Established the normative anthropometric ranges still used in modern facial-analysis tooling: average canthal tilt, gonial angle, facial thirds, and bizygomatic-to-midface ratios.
Liang, Lin, Jin, Xie & Li (2018) · ICPR (arXiv:1801.06345)
5,500 face photos each rated for attractiveness by 60 human raters — the standard academic benchmark for facial beauty prediction. We use it to validate our own scoring: our Impression Percentile model reaches cross-validated r ≈ 0.80 against the averaged human ratings (see "Our own validation" below).
Our own validation · published 2026-07-02
Method. We ran our production pipeline — the same 68-point landmark detector every scan uses — against the SCUT-FBP5500 academic benchmark (Liang et al., 2018): 5,500 face photos, each independently rated for attractiveness by 60 human raters. We compared our scores to the averaged human ratings using 5-fold cross-validation, so every reported number is measured on faces the model never saw during fitting.
Finding 1 — our original geometry composite failed, and we say so. The 17-metric weighted average we previously used as the overall score showed no positive correlation with human attractiveness ratings (r ≈ −0.33). The individual measurements are real geometry; the blended composite simply does not predict how people rate a face. That is why the report now presents the 17 metrics as measurements — not as an attractiveness verdict.
Finding 2 — the replacement passes. Our Impression Percentile model, built on a 128-dimension facial appearance representation, reaches a cross-validated correlation of r ≈ 0.80 with the averaged 60-rater human judgments (n = 1,566 benchmark faces; consistent across male and female subsets). For reference, published deep-learning models on this benchmark reach r ≈ 0.85–0.90, and simple geometric-feature models reach r ≈ 0.55–0.65.
July 2026 update — v2. A second-generation kernel model, validated the same way, reaches a 5-fold cross-validated correlation of r ≈ 0.836 (percentiles calibrated on out-of-fold predictions). v2 is served to Pro subscribers; v1 (r ≈ 0.80) remains the model in the one-time report.
Scope and limits. The validation covers the Impression Percentile only. It measures agreement with how people rate photos on this benchmark — not dating outcomes, not real-world results, and the benchmark skews toward controlled, front-facing photos. Your number moves with lighting, angle, and expression, which is exactly why the report treats it as photo feedback rather than a verdict on your face.
To our knowledge, no other consumer face-rating tool publishes any validation of its scoring against human ratings. If a competitor publishes theirs, we will link it here.
The face-perception literature is well-established but spread across psychology, anthropology, and economics journals. A single lookup that maps each study to the RealSmile page that uses it makes the citation chain checkable in one click. The studies above are the load-bearing references for the 17-metric audit, the dating-photo audit, the LinkedIn headshot audit, and the four long-tail measurement guides.
For the original-data companion to this index, see the State of Looksmaxxing 2026 data report, which publishes RealSmile's aggregated face-scan distributions alongside the published-research baselines listed above.