Baby Name Generator

What the generator actually does

There is no name-inventing algorithm here. The generator holds the SSA's 2025 top 1,000 girl names and top 1,000 boy names, plus 7 decade snapshots (1955–2015, the top 200 names per sex for each single year). Your six controls narrow that pool: gender selects one sex's list or both, the starting letter keeps only names whose SSA spelling begins with it, length keeps one of three classes counted on that spelling, the era swaps in a different year's list, and the popularity tier keeps a rank range within that list. The count slider sets how many names to draw, from one to 20.

The draw itself uses your browser's cryptographic random number generator. Random bytes are mapped onto the filtered pool by rejection sampling — the minimal number of bits that covers the pool size is drawn, the excess bits are masked, and any value at or past the pool size is discarded and redrawn — so every matching name is exactly equally likely, with no modulo bias. Multi-name draws run a partial Fisher–Yates shuffle, which is why a single spin never repeats a name. The sampling code accepts an injected byte source, and that is how the automated tests pin the exact mapping. The full walk-through is in the guide how the name generator samples.

Each result row carries three facts from one SSA year file: the name as the SSA spells it, its rank within its sex for the era's year, and the number of Social Security card applications that recorded it. Because the SSA ranks each sex separately, a spelling that appears on both lists has two ranks and two counts. In 2025, 82 spellings sit on both the girls' and the boys' top-1,000 lists; Noah, for instance, is #2 for boys with 20,358 babies and #624 for girls with 468. When both genders are selected, every row shows which list it came from.

The 2025 data at a glance

The 2025 girls' list starts at Olivia, #1 with 13,544 babies, passes #100 Juniper at 2,618, and stops at #1,000 Harmoni with 252 — a list of 1,000 names covering 1,182,238 registered births. The boys' list starts at Liam, #1 with 20,818 babies, passes #100 Myles at 3,511, and stops at #1,000 Langston with 227 — 1,000 names covering 1,387,686 births. Names ranked past #1,000 are outside the committed depth of these two lists, so the generator cannot draw them in the 2025 era.

Counted on the SSA spelling, the 2025 girls' list splits into 146 short names of four letters or fewer, 723 medium names of five to seven letters, and 131 long names of eight letters or more. The boys' list splits into 183 short, 739 medium, and 78 long. These are the exact pools the length filter selects from in the latest era.

By starting letter, the largest share of 2025 girl births in the top 1,000 goes to A: 170 names that together hold 16.7% of the list's births, ranking it first of the 26 initials. It is also the initial with the most girl names in the list. For boys the largest share goes to J: 91 names holding 11.2% of the births. The initial with the most boy names in the list is A, with 110. No girl name in the 2025 top 1,000 begins with U; the letter page for U still lists 32 names, the best of them ranked #2,456.

Eras and depths

The Era menu offers 8 choices, and each is one SSA year file, never a blend of years. The latest era is the full top 1,000 per sex for 2025. Every decade era is a single snapshot year — "the 2010s" means registered in 2015 — and reaches only the top 200 names per sex, which is why the menu labels name the snapshot year. The table lists the eras in menu order with the #1 name of each sex and its count for that year.

On the boys' side, Michael is #1 in 5 of the 7 snapshots (1955, 1965, 1975, 1985 and 1995); on the girls' side, Jessica is #1 in 2 of the 7 snapshots (1985 and 1995); in 2025 the #1 names are Liam and Olivia. The leading initial is likewise a per-list fact. In the 1955 snapshot the largest share of top-200 girl births belonged to D at 13.8%, and of boy births to J at 16.2%; in the 2025 top 1,000 the leaders are A and J. Those two depths differ, so the figures are stated against their own lists rather than compared directly. A holds the largest share of top-200 girl births in 5 of the 7 snapshots, and J the largest share of boy births in 7. The per-snapshot table for every initial is in the guide first-letter trends since 1955 , and the snapshots themselves are explained in decade snapshots explained.

Filters that admit what the data can't answer

The popularity tiers are rank ranges in the selected era's own list: top 10, top 100, ranks 101–500, and ranks 501–1,000. A decade snapshot stops at rank 200, so the uncommon (ranks 501–1,000) tier begins past the end of the list and is structurally empty there; the ranks 101–500 tier reaches only rank 200 in those eras. The generator reports both cases in plain words instead of quietly substituting different names.

Pool sizes are concrete. Choose girl names, the letter A and the short length in the 2025 era and the pool holds 20 names; choose the top-10 tier with both genders and it holds 20, so a 20-name spin returns all of them shuffled. Some combinations hold nothing: of the 78 letter-by-length combinations in the 2025 girls' top 1,000, 11 are empty (no girl name in that list begins with B and has four letters or fewer), and in the boys' top 1,000, 9 are empty (none begins with I and has eight letters or more). An empty result is a real result. A name missing from the pool is not necessarily unused: the SSA excludes names given fewer than 5 times to one sex in a year, spelling variants are ranked separately, and the committed lists stop at the depths above.

Browse by starting letter

Every initial has its own page for each sex, 52 pages in all, each holding up to 50 names from the 2025 file with their overall rank and count. The girls' pages carry 1,266 names between them and the boys' pages 1,289; the lists are never padded, so the girls' pages for Q (34 names) and U (32 names) stop short of 50, and the boys' pages for Q (39 names) stop short — those are all the qualifying names the SSA file holds for those initials. Each letter page links back into the generator with its gender and letter preset.

Girl names A–Z

Boy names A–Z

The two top-100 tables sit alongside: the top 100 girl names of 2025 and the top 100 boy names of 2025, each a real rank and count table with its own A–Z strip.

Start here

The guides explain the dataset and the conventions this site uses, and every figure in them is computed from the same committed files at build time:

• How SSA baby-name data works — the source archive, the build pipeline, and the nine qualifications the SSA attaches.
• Reading ranks and counts — what a rank and a count literally mean, alphabetical ties, and the spread inside the 2025 lists.
• Spelling variants chart separately — why each spelling has its own row, and what the SSA strips before counting.
• Decade snapshots explained — why each era is a single year, the 200-name depth, and each snapshot's #1 names.
• First-letter trends since 1955 — every initial's share of top-200 births in each snapshot, for both sexes.
• Short, medium, and long names — the three length classes and how the 2025 lists and the snapshots split across them.
• How the name generator samples — rejection sampling, the partial Fisher–Yates shuffle, the filters, and empty results.
• What this site does not publish — meanings, origins, uniqueness scores and AI-made names — and why none appear here.

The methodology page documents the source archive, the build pipeline, and the integrity tests over the committed files, and the about page states what the site covers and what it deliberately leaves out.

Frequently asked questions

Source: every name, rank, and count on this page comes from the U.S. Social Security Administration's national baby-names dataset (1955–2025 data, from Social Security card applications). It is public-domain U.S. government data; names given fewer than 5 times in a year are excluded by the SSA, spelling variants are counted separately, and the data covers U.S. births only. Full caveats on the methodology page.