Free AI face rating. Symmetry, proportions, jawline, and shape — measured from 478 facial landmarks, scored 0–100, processed in your browser.
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Most people score between 70 and 85. Faces commonly rated as attractive in research typically score 80–95, not 100 — perfect mathematical alignment is rare and not necessary for being attractive. Where you fall on this scale:
90–100 — Showstopper
Top 5% of analyzed faces. Striking proportions across every measured component — symmetry, thirds, fifths, and golden ratio all in their aesthetic ranges. Even faces commonly rated as highly attractive rarely hit 95+.
80–89 — Standout
Top 15%. Strong harmony with standout features. Most components hit aesthetic ideals; small deviations elsewhere keep the face distinctive rather than generic.
70–79 — Glow Up
Top 35%. Above-average balance with clear room to push higher. Several components hit ideal ranges and a few well-defined levers (symmetry exercises, grooming, photo angles) can move the score into the 80s.
60–69 — Rising
The median range — where most people score. Solid foundation with the most upside per change: small improvements in lighting, expression, symmetry, and grooming all stack visibly here.
Below 60 — Foundation
Distinctive features outside the average band. The score measures distance from classical Western canon and often misses faces that are genuinely attractive in ways the algorithm can't read — distinctive bone structure, expression, or proportions outside the trained range. Treat the number as one signal, not a verdict.
Your score is a weighted sum of four mathematical components from peer-reviewed attractiveness research. The weights reflect how strongly each component correlates with attractiveness ratings in published studies.
How closely the left and right sides of your face mirror each other. Symmetry has the strongest single correlation with perceived attractiveness in published research, hence the largest weight. Computed from bilateral landmark pairs measured against a stable facial midline.
How evenly your face divides into three vertical sections — hairline to brow, brow to nose base, nose base to chin. The classical aesthetic ideal is roughly equal thirds. A high weight reflects the strong consensus across cosmetic surgery and aesthetic anthropometry that thirds balance signals proportional harmony.
How the face divides horizontally into five eye-width segments — ear to outer eye, outer to inner eye (one eye width), inner-eye gap (one eye width), and so on across to the other ear. Fifths balance is a centuries-old canon for upper-face proportion.
How closely your face length-to-width ratio matches phi (1.618). The lowest weight in our formula because the 2024 evidence base shows this ratio has weaker links to perceived attractiveness than symmetry or proportional balance — included for completeness rather than as a primary signal.
Several decades of research have converged on a few well-supported findings about what predicts perceived attractiveness across observers and cultures.
What's well-supported
What an AI photo test misses
Be honest with yourself about what this tool can and can't do
Front-facing, eye-level camera
Tilted angles distort vertical proportions and inflate apparent asymmetry. Hold the camera at eye level and roughly arm's length away.
Neutral expression
A relaxed, neutral expression gives the most stable measurement. Smiles dramatically alter mouth, cheek, and jaw landmarks and tend to lower the symmetry component.
Hair pulled back
Hair covering the hairline or jaw outline blocks landmark detection. Tie hair back so the full face contour is visible.
Avoid wide-angle selfies
Phone selfie cameras distort proportions, especially close to the lens. Use a back camera at arm's length, or have someone else take the photo from a few feet away.
Even, soft lighting
Strong shadows shift apparent feature edges and exaggerate asymmetry. Diffused front lighting (window light works well) gives the cleanest measurement.
Yes — with the formula shown. We measure four well-defined mathematical components (symmetry, facial thirds, facial fifths, golden ratio) that are documented predictors of perceived attractiveness in published research, then combine them into a 0–100 score. Most popular AI beauty tests give a black-box rating with no methodology; we show exactly how every point is calculated.
Most people score between 70 and 85. Scores of 80+ indicate strong proportional balance and put you in roughly the top 30%. Faces commonly rated as highly attractive in research typically score in the 80–95 range rather than at 100 — perfect alignment across all four components is statistically rare and not a precondition for being attractive.
Two key differences. First, we show the formula: symmetry 35% + thirds 25% + fifths 25% + golden ratio 15%. Most competitor tools give a black-box 1–10 score with no methodology. Second, we use real MediaPipe 478-landmark geometry — measurements computed from your actual face proportions, not vibes-based vision-LLM hallucinations. The math is reproducible: the same photo gets the same score every time.
Some components, yes. Symmetry can be improved through targeted facial exercises and breaking habitual patterns (one-sided sleeping, chewing) — see our facial exercises guide. Soft tissue proportions (mid-face, lower face) shift with weight changes, fillers, and skin care. Skeletal proportions (face width, jaw width, eye spacing) are fixed after early adulthood. Hairstyle, grooming, and makeup can change the visual reading of all four components without changing the underlying measurements.
Three common reasons. First, photo conditions: tilted angles, smiles, asymmetric expressions, and poor lighting all reduce scores significantly. Try a neutral, front-facing photo with even lighting. Second, the score is mathematically strict — most attractive faces don't score above 90 in any objective system. Third, the score measures distance from classical Western canon, which doesn't capture every form of attractiveness; some highly attractive faces deviate from these ratios.
The aesthetic-ideal ranges used here come from cosmetic surgery literature and Western anthropometric studies, which have well-documented Eurocentric bias. The tool doesn't classify by race or gender, but the ratio targets reflect a particular aesthetic tradition. Faces from non-European populations may score lower not because they're less attractive but because their natural proportions deviate from these specific norms. Treat the score as a measurement against one tradition, not a universal judgment.
It can be a useful tiebreaker if you have several similar photos and want to pick the one with the best lighting and angle (which strongly affect the score). But research on dating-app photo selection consistently finds that warmth, approachability, and a genuine smile predict matches better than mathematical harmony. A photo with a slightly lower harmony score but a genuine smile usually outperforms a higher-harmony but neutral one.
Decades of research (Rhodes, 2006; Little, 2014; and others) consistently identify several factors that correlate with attractiveness ratings: bilateral symmetry, averageness (faces close to the population mean), sexual dimorphism (gender-typical features), and clear skin. Beyond these, expression, behavior, vocal qualities, and cultural context strongly modulate perceived attractiveness. The harmony score captures the symmetry + proportional aspects; the others require a real human, not a photo.