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Arabic name gender

Arabic script resolves through a consonant skeleton index rather than a guessed transliteration. That design choice is the reason three specific names stopped returning confident wrong answers.

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Names measured
200
Coverage
93.5%
Accuracy when answered
87.7%
End-to-end
82.0%

Measured 28 August 2026 on a fixed, reproducible fixture. Not a population sample — a fixed input anyone can rerun against us or against a competitor.

Why the skeleton, and not a spelling guess

Arabic script writes consonants and leaves most short vowels implicit, so a single written form corresponds to a family of Latin spellings. There are two ways to bridge that. You can guess a specific Latin spelling and look it up, or you can look up the consonant skeleton and use the combined evidence of every name that matches it.

The skeleton is the stronger signal, and we have the failures to prove it. When speculative full spellings were given priority, علي resolved through an invented "lya" and came back female; خالدة came back male; نورا came back male. In all three the skeleton was right and the single guessed spelling was wrong.

A single spelling guess is not stronger evidence than the whole set of names it might correspond to. Today a full match is only preferred when it agrees with the skeleton and brings a real sample with it.

Real output, country hint SA

Arabic-script inputs report source: script, which tells you the answer came through the bridge rather than a direct match. That distinction is worth keeping in your pipeline, because the bridge is one more place an error can enter.

Input Gender Probability
محمد (Mohammed) male 100
فاطمة (Fatima) female 100
علي (Ali) male 98
خالدة (Khalida) female 100
نورا (Noura) female 100
Mohammed male 95

Transliteration variance in Latin input

Mohammed, Muhammad, Mohamed, Mohammad and Muhammed are the same name in five documents. Latin-script Arabic names therefore miss more often through spelling variance than through genuine absence. Near-spellings resolve via fuzzy matching and matched_as reports which entry was used.

Where you hold the Arabic script form, send that instead — it collapses the whole variant family into one lookup.

Honest limits

Arabic is our weakest measured coverage among the scripts we do support, and the misses are a data gap rather than a bridge failure: when we answer, we are usually right. Definite articles and compound forms (Abd al-, Abu) attach to the given name in ways that vary by country, and RTL text pasted from documents often carries directional marks that should be stripped before sending.

Questions

Do diacritics matter?

No. Arabic diacritics are preserved rather than stripped globally, and the skeleton index does the matching.

Which country code should I pass?

The one your record actually carries. Naming conventions differ substantially across the Arabic-speaking world, and none of those countries publish registration counts.

Why does one name show observations and another none?

Because a skeleton can land on entries that came from a counted source. Where it does, total_names is non-zero and confidence rises accordingly.

Is Persian or Urdu supported?

They share the script but not the name stock, and we do not measure them separately. Test on your own data before relying on it.

Related pages

Turkish name gender

Predict gender from a Turkish name. Dotted and dotless i handling, the genuinely unisex names, and why correct Turkish answers are still marked unverified.

Indian name gender

Predict gender from an Indian name in romanised or Devanagari form. This is our strongest non-Latin market, and this page shows the measured numbers.

Gender probability by name

Every name lookup returns a probability, a sample size and a confidence tier. What each one measures, how the tiers are set, and where to put your threshold.

Our coverage, script by script — including where we fail

A reproducible benchmark across 4,610 names, 25 countries and nine writing systems. Two scripts return almost nothing, and we publish those numbers too.

probability, confidence and total_names: reading a gender response properly

Reading the gender field alone discards everything that says whether to believe it. What each response field means and the thresholds behind confidence.

Check it against your own list

Every number on this page is reproducible with a free key. If your data breaks it, that is the more interesting result.