LOOKSMAXING.fit

Methodology · rubric v2.2

Sixteen sub-factors. One formula. No black box.

A score you can't interrogate is a horoscope. The model only does perception - it scores sixteen named sub-factors against a fixed written rubric. Every number you see (feature scores, your overall, your potential) is then computed by us with a published weighted formula. The model never hands you a number it made up.

The five features and their sub-factors

Jawline

22% of overall
  • Definition - Visibility of the jaw-to-neck transition.
    Partly40%
  • Under-chin - Fullness under the chin (body-fat and hydration responsive).
    Movable35%
  • Contour - Underlying jaw shape as presented (not changeable by habit).
    Structural25%

Skin

24% of overall
  • Clarity - Visible breakouts and blemishes.
    Movable35%
  • Evenness - Redness and tone uniformity.
    Movable25%
  • Texture - Surface smoothness and visible pores.
    Partly20%
  • Hydration - Dull and dry versus healthy and supple.
    Movable20%

Eyes

20% of overall
  • Under-eye - Dark circles and puffiness of the under-eye area.
    Movable45%
  • Brows - Brow grooming and upkeep (not brow shape genetics).
    Movable30%
  • Freshness - How rested and alert the eye area looks - a fatigue signal, never an emotion read.
    Movable25%

Balance

14% of overall
  • Balance - Left-right evenness as presented in a front-facing photo.
    Partly45%
  • Grooming evenness - Evenness of grooming across the face.
    Movable30%
  • Proportion - Presented facial proportions (not changeable by habit).
    Structural25%

Hair

20% of overall
  • Cut - Quality and freshness of the current cut.
    Movable40%
  • Condition - Health, shine, and frizz.
    Movable35%
  • Style fit - How well the style frames the face as presented.
    Movable25%

Movable, partly, or structural

Every sub-factor is tagged by how much a 90-day protocol can actually move it. Movable sub-factors (skin clarity, under-chin fullness, brow upkeep) respond to grooming and lifestyle. Structural ones (bone contour, facial proportion) do not - so we lock them and they contribute zero to your potential. Your potential is your current overall plus only the headroom on movable sub-factors, never raised above 88 on any single one. That is why our potential is a promise we can keep, not a number designed to flatter you.

Confidence, not false precision

We run the scoring several times and measure how much the passes agree. Tight agreement reads as high confidence; lighting, angle, or a hat that blurs a sub-factor lowers it - and we tell you, rather than printing a precise-looking number we don't trust. Low-confidence reads come with a nudge to retake in even light.

How a score is produced

  1. 01Your photo is normalized deterministically - same resize, same crop, same processing every time, so identical photos produce identical model input.
  2. 02The model scores sixteen sub-factors against fixed written band definitions (the rubric) - pure perception, no overall, no improvised judgment. The rubric is versioned; your score is stamped with the version that produced it.
  3. 03Inference runs with zero sampling randomness.
  4. 04The full pass runs three times and we keep the median per sub-factor. If the passes disagree, we automatically run more passes before trusting the number, rather than reporting false precision.
  5. 05The app - not the model - computes your feature scores, overall, potential, and confidence from those sub-scores using the published weighted formula below.
  6. 06The photo is deleted from memory before the response returns. Only the numbers persist.

The result: scan the same photo twice and you get the same score. Why most apps can't say that →

What we will never score

The output schema physically has no fields for these - it is not a policy toggle, the model cannot return them:

Some competitors advertise "masculinity" scores. We think that's both scientifically hollow and corrosive - and we built the schema so we can't drift into it.

The honest caveats

This is a measurement of a photo, not of you - lighting, angle, and camera quality are part of what any vision model sees, which is why re-scans ask for consistent conditions. Scores are rubric-anchored opinions of an AI model, useful for tracking your own change over time - they are not clinical assessments, percentile claims against humanity, or anything medical. For skin or health concerns, see a professional, not an app.

Photo handling details: what happens to your photo.

Get scored - free →