Historical Names With Lower Recorded Use
Compare exact spellings recorded in both 1990 and 2025. A lower count indicates a decline between those two observations; a missing record cannot establish that a name has disappeared.
By Marvin Tang · Content and calculations reviewed October 27, 2026.
National data scope: 65,411 imported name/sex/year records across 1880–2025. This is a selected subset of SSA records, with narrower historical coverage and catalog/rank filters. A missing row does not establish zero use or fewer than five uses. Figures below describe the stated selection. Data coverage and limits.
Names with smaller counts at the later observation
The table includes only exact spelling-and-sex combinations with a row in both comparison years. It ranks those observed declines by percentage, with larger earlier counts breaking ties. It is a comparison within the available selection, not an exhaustive ranking of all declining US names.
| Name | SSA sex list | 1990 count | 2025 count | Decrease | Latest stored rank |
|---|---|---|---|---|---|
| Brittany | F | 36,537 | 281 | 99.2% | #928 |
| Jessica | F | 46,486 | 424 | 99.1% | #665 |
| Megan | F | 20,259 | 301 | 98.5% | #889 |
| Amanda | F | 34,413 | 601 | 98.3% | #493 |
| Stephanie | F | 24,864 | 543 | 97.8% | #557 |
| Jennifer | F | 22,236 | 501 | 97.7% | #586 |
| Tiffany | F | 13,162 | 304 | 97.7% | #880 |
| Chelsea | F | 12,784 | 319 | 97.5% | #851 |
| Kyle | M | 22,710 | 594 | 97.4% | #509 |
| Christina | F | 11,928 | 352 | 97.0% | #770 |
| Kelsey | F | 9,494 | 335 | 96.5% | #814 |
| Amber | F | 15,866 | 576 | 96.4% | #520 |
| Lauren | F | 20,507 | 777 | 96.2% | #401 |
| Danielle | F | 14,339 | 550 | 96.2% | #549 |
| Kelly | F | 8,137 | 319 | 96.1% | #852 |
| Ashley | F | 45,560 | 1,829 | 96.0% | #164 |
| Erin | F | 7,988 | 327 | 95.9% | #833 |
| Dustin | M | 8,457 | 365 | 95.7% | #729 |
| Corey | M | 7,691 | 327 | 95.7% | #778 |
| Nicole | F | 17,953 | 803 | 95.5% | #383 |
| Kayla | F | 17,538 | 838 | 95.2% | #364 |
| Lisa | F | 5,347 | 256 | 95.2% | #991 |
| Justin | M | 30,650 | 1,512 | 95.1% | #233 |
| Michelle | F | 13,424 | 661 | 95.1% | #465 |
| Jamie | F | 6,509 | 316 | 95.1% | #858 |
| Jeffrey | M | 10,980 | 544 | 95.0% | #552 |
| Sean | M | 12,018 | 616 | 94.9% | #489 |
| Melissa | F | 14,000 | 747 | 94.7% | #420 |
| Brian | M | 16,933 | 979 | 94.2% | #339 |
| Gregory | M | 8,377 | 493 | 94.1% | #593 |
What this comparison can establish
For a displayed spelling, the later observed count is smaller than the earlier count. The calculation is (earlier count minus later count) divided by the earlier count. Both counts are required and the denominator must be positive. There is no substitute denominator for an absent or zero baseline.
Two observations cannot establish when a decline began, whether it was continuous, or which year was the name’s true peak. Use the individual history to inspect the intervening observations, while remembering that this site’s historical import is incomplete.
Low rank does not mean a name has died
A name outside the top 500 can still be used by many families. It may also remain common among adults or in another country. A gap in this site’s records may result from import selection, a rank cutoff, privacy suppression in the source, or a different spelling. These possibilities require different evidence and should not be collapsed into a zero.
For a family considering a less common historical name, investigate pronunciation, associations, and whether the spelling has a documented history. A lower recent count is one piece of that decision; it is not a measure of the name’s quality or cultural survival.
Sources and interpretation
Popularity counts come from the US Social Security Administration baby-name files. SSA records applications for Social Security cards and separates exact spellings and recorded sex. Its public files apply privacy limits; this site applies additional import limits. National counts do not identify families, religion, ethnicity, gender identity, or the reason a name was chosen. Name origins are separate editorial fields, not SSA findings.
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