Most Popular Baby Names In New Hampshire
The 100 most-used girls' and boys' names among recorded births from New Hampshire, 2016–2025 — 80,091 applications in that window. Below them: the names New Hampshire uses far more than the rest of the country.
Girls’ names
- 1Charlotte8622.4%
- 2Olivia7072.0%
- 3Emma5721.6%
- 4Amelia5541.5%
- 5Evelyn5521.5%
- 6Harper5091.4%
- 7Sophia4731.3%
- 8Nora4461.2%
- 9Ava4311.2%
- 10Isabella4111.1%
- 11Eleanor3781.0%
- 12Abigail3551.0%
- 13Madison3410.9%
- 14Grace3370.9%
- 15Violet3250.9%
- 16Avery3210.9%
- 17Scarlett3190.9%
- 18Lillian3150.9%
- 19Lily3070.9%
- 20Mia3050.8%
- 21Isla3030.8%
- 22Ella2970.8%
- 23Hazel2950.8%
- 24Natalie2920.8%
- 25Aurora2800.8%
- 26Lucy2800.8%
- 27Maeve2790.8%
- 28Penelope2770.8%
- 29Willow2690.7%
- 30Hannah2620.7%
- 31Riley2600.7%
- 32Ellie2570.7%
- 33Elizabeth2560.7%
- 34Madelyn2420.7%
- 35Emily2400.7%
- 36Aria2350.7%
- 37Addison2310.6%
- 38Chloe2290.6%
- 39Layla2260.6%
- 40Stella2190.6%
- 41Piper2160.6%
- 42Kinsley2130.6%
- 43Autumn2120.6%
- 44Josephine2120.6%
- 45Paisley2070.6%
- 46Quinn2050.6%
- 47Vivian2040.6%
- 48Madeline2010.6%
- 49Zoey2010.6%
- 50Kennedy1980.5%
- 51Cora1930.5%
- 52Mackenzie1930.5%
- 53Aubrey1920.5%
- 54Adeline1910.5%
- 55Eloise1910.5%
- 56Hadley1910.5%
- 57Luna1910.5%
- 58Maya1900.5%
- 59Emilia1890.5%
- 60Claire1880.5%
- 61Lydia1880.5%
- 62Everly1870.5%
- 63Isabelle1810.5%
- 64Mila1800.5%
- 65Alice1770.5%
- 66Sadie1770.5%
- 67Sophie1720.5%
- 68Anna1710.5%
- 69Savannah1710.5%
- 70Clara1670.5%
- 71Audrey1640.5%
- 72Ivy1610.4%
- 73Zoe1590.4%
- 74Lyla1550.4%
- 75Margaret1500.4%
- 76Sofia1480.4%
- 77Hailey1420.4%
- 78Leah1420.4%
- 79Julia1370.4%
- 80Ruby1370.4%
- 81Eliana1360.4%
- 82Caroline1340.4%
- 83Eliza1340.4%
- 84Brooke1330.4%
- 85Liliana1310.4%
- 86Gianna1290.4%
- 87Rose1280.4%
- 88Emerson1270.4%
- 89Brooklyn1250.3%
- 90Nova1250.3%
- 91Elena1240.3%
- 92Gabriella1230.3%
- 93Molly1200.3%
- 94Bailey1170.3%
- 95Freya1170.3%
- 96Iris1140.3%
- 97Peyton1140.3%
- 98Rylee1110.3%
- 99Norah1100.3%
- 100Juniper1080.3%
Boys’ names
- 1Oliver7591.7%
- 2Henry7061.6%
- 3Theodore6701.5%
- 4Liam6621.5%
- 5Owen6531.5%
- 6Benjamin6471.5%
- 7William6201.4%
- 8Jackson6011.4%
- 9Noah5871.3%
- 10Lucas5811.3%
- 11Jack5801.3%
- 12James5571.3%
- 13Logan5071.2%
- 14Wyatt5001.1%
- 15Mason4991.1%
- 16Lincoln4561.0%
- 17Levi4471.0%
- 18Thomas4050.9%
- 19Wesley4020.9%
- 20Carter3950.9%
- 21Elijah3740.8%
- 22Charles3580.8%
- 23Colton3550.8%
- 24Michael3520.8%
- 25John3510.8%
- 26Joseph3510.8%
- 27Alexander3410.8%
- 28Grayson3330.8%
- 29Jacob3330.8%
- 30Julian3310.8%
- 31Nolan3210.7%
- 32Samuel3190.7%
- 33Connor3140.7%
- 34Maverick3080.7%
- 35Leo3060.7%
- 36Jameson3030.7%
- 37Ethan3000.7%
- 38Parker2930.7%
- 39Cameron2870.7%
- 40Hunter2870.7%
- 41Matthew2770.6%
- 42Bennett2740.6%
- 43Daniel2710.6%
- 44Luke2700.6%
- 45Landon2650.6%
- 46Ryan2640.6%
- 47Caleb2630.6%
- 48Declan2610.6%
- 49Miles2590.6%
- 50Gabriel2570.6%
- 51Rowan2550.6%
- 52Sawyer2550.6%
- 53Hudson2540.6%
- 54Emmett2530.6%
- 55Cole2510.6%
- 56Everett2440.6%
- 57Luca2430.6%
- 58Cooper2410.5%
- 59Asher2360.5%
- 60Anthony2340.5%
- 61Isaac2310.5%
- 62Robert2290.5%
- 63Weston2280.5%
- 64Jaxson2220.5%
- 65Andrew2200.5%
- 66Greyson2200.5%
- 67Calvin2080.5%
- 68Ryder2060.5%
- 69David1990.5%
- 70Aiden1980.4%
- 71Christopher1980.4%
- 72Ezra1960.4%
- 73Dylan1910.4%
- 74Silas1910.4%
- 75Harrison1900.4%
- 76Brayden1870.4%
- 77Carson1870.4%
- 78Jaxon1860.4%
- 79Maxwell1810.4%
- 80Austin1780.4%
- 81Chase1760.4%
- 82Gavin1760.4%
- 83Myles1760.4%
- 84Eli1750.4%
- 85Nathan1750.4%
- 86Elliot1720.4%
- 87Elias1700.4%
- 88George1700.4%
- 89Zachary1700.4%
- 90Bentley1640.4%
- 91Brooks1590.4%
- 92Evan1560.4%
- 93Griffin1560.4%
- 94Nicholas1550.4%
- 95Finn1540.3%
- 96Isaiah1530.3%
- 97Camden1500.3%
- 98Joshua1500.3%
- 99Beau1490.3%
- 100Easton1490.3%
New Hampshire's signature names
Names used at least 2× as often in New Hampshire as across all states combined, 2016–2025. The multiple compares New Hampshire's share of listed births with the same share pooled across every state — the closest thing to "how New Hampshire does it differently" the data can support.
Girls’ names
- Maeve5.3× · 279 recorded
- Brooke3.9× · 133 recorded
- Maisie3.6× · 82 recorded
- Fiona3.4× · 98 recorded
- Mackenzie3.2× · 193 recorded
- Delaney3.2× · 105 recorded
- Mabel3.1× · 75 recorded
- Piper2.9× · 216 recorded
- Eloise2.9× · 191 recorded
- Isabelle2.9× · 181 recorded
- Thea2.9× · 80 recorded
- Nora2.8× · 446 recorded
- Hadley2.8× · 191 recorded
- Octavia2.8× · 66 recorded
- Molly2.7× · 120 recorded
- Freya2.7× · 117 recorded
- Vera2.7× · 92 recorded
- Wren2.7× · 75 recorded
- Vivian2.6× · 204 recorded
- Madeline2.6× · 201 recorded
- Mckenna2.6× · 72 recorded
- Charlotte2.5× · 862 recorded
- Isla2.5× · 303 recorded
- Natalie2.5× · 292 recorded
- Madelyn2.5× · 242 recorded
Boys’ names
- Colby7.6× · 95 recorded
- Finnegan5.2× · 102 recorded
- Callan3.8× · 90 recorded
- Griffin3.4× · 156 recorded
- Wesley3.3× · 402 recorded
- Odin3.3× · 82 recorded
- Cole3.1× · 251 recorded
- Colin3.1× · 117 recorded
- Brady3.1× · 112 recorded
- Callum3.1× · 111 recorded
- Finley3× · 103 recorded
- Ronan2.9× · 105 recorded
- Malcolm2.9× · 85 recorded
- Jameson2.8× · 303 recorded
- Wilder2.8× · 52 recorded
- Colton2.7× · 355 recorded
- Declan2.7× · 261 recorded
- Emmett2.7× · 253 recorded
- Calvin2.7× · 208 recorded
- Rory2.7× · 88 recorded
- Keegan2.7× · 53 recorded
- Owen2.6× · 653 recorded
- Parker2.6× · 293 recorded
- Sawyer2.6× · 255 recorded
- Elliot2.6× · 172 recorded
All-time favorites, 1910–2025
The most-used names across everything New Hampshire has recorded since 1910 — a very different list, dominated by the high-birth, low-variety decades of the mid-century.
Girls’ names
- 1Mary8,5361.7%
- 2Jennifer6,8001.4%
- 3Elizabeth6,7651.4%
- 4Sarah5,7161.2%
- 5Patricia5,2521.1%
- 6Susan5,1211.0%
- 7Linda5,1071.0%
- 8Barbara4,9051.0%
- 9Jessica4,8411.0%
- 10Emily4,5480.9%
- 11Nancy4,1920.8%
- 12Lisa3,9680.8%
- 13Amanda3,7280.8%
- 14Donna3,5700.7%
- 15Karen3,5600.7%
- 16Margaret3,5480.7%
- 17Rebecca3,4750.7%
- 18Dorothy3,3870.7%
- 19Sandra3,3830.7%
- 20Kathleen3,2910.7%
- 21Melissa3,2780.7%
- 22Katherine3,2460.7%
- 23Heather3,1400.6%
- 24Samantha3,1400.6%
- 25Ashley3,1070.6%
- 26Nicole3,0790.6%
- 27Amy3,0140.6%
- 28Michelle3,0090.6%
- 29Carol2,9950.6%
- 30Emma2,9580.6%
- 31Hannah2,8820.6%
- 32Diane2,8290.6%
- 33Olivia2,8230.6%
- 34Deborah2,7700.6%
- 35Stephanie2,7690.6%
- 36Kimberly2,6880.5%
- 37Christine2,6240.5%
- 38Helen2,6060.5%
- 39Ruth2,5900.5%
- 40Rachel2,5690.5%
- 41Laura2,5380.5%
- 42Abigail2,5200.5%
- 43Pauline2,5080.5%
- 44Catherine2,4610.5%
- 45Doris2,3870.5%
- 46Cynthia2,3400.5%
- 47Judith2,2880.5%
- 48Kelly2,2800.5%
- 49Megan2,2460.5%
- 50Charlotte2,2430.5%
Boys’ names
- 1Robert19,7223.5%
- 2Michael16,8753.0%
- 3John16,2542.9%
- 4David14,3682.6%
- 5Richard13,4722.4%
- 6James13,3372.4%
- 7William12,3952.2%
- 8Christopher9,1011.6%
- 9Matthew8,9761.6%
- 10Thomas8,5691.5%
- 11Joseph8,4221.5%
- 12Daniel8,0161.4%
- 13Paul7,4161.3%
- 14Charles6,2821.1%
- 15Donald6,0781.1%
- 16Ryan6,0231.1%
- 17Andrew5,9261.1%
- 18Brian5,8371.0%
- 19Joshua5,7281.0%
- 20George5,5841.0%
- 21Timothy5,4111.0%
- 22Mark5,2981.0%
- 23Nicholas5,2600.9%
- 24Benjamin5,1790.9%
- 25Peter5,1250.9%
- 26Scott4,9640.9%
- 27Kevin4,8610.9%
- 28Jeffrey4,7810.9%
- 29Jason4,7800.9%
- 30Stephen4,5980.8%
- 31Edward4,5950.8%
- 32Steven4,5400.8%
- 33Jacob4,4720.8%
- 34Raymond4,4050.8%
- 35Kenneth4,2420.8%
- 36Jonathan4,1680.7%
- 37Ronald4,1610.7%
- 38Eric3,7850.7%
- 39Tyler3,7280.7%
- 40Roger3,4220.6%
- 41Anthony3,3290.6%
- 42Zachary3,3260.6%
- 43Alexander3,2480.6%
- 44Adam3,2290.6%
- 45Nathan3,2120.6%
- 46Patrick3,1040.6%
- 47Arthur3,0740.6%
- 48Justin3,0720.6%
- 49Samuel3,0520.5%
- 50Gary3,0320.5%
State data starts in 1910 (national data goes back to 1880) and is censored per state and year: a name needs 5 uses in New Hampshire in a year to appear at all. That censoring means state counts never sum to the national total, and it bites hardest on uncommon names in small states.
Counts are based on U.S. births and are tracked separately for girls and boys. Names used fewer than 5 times in a year aren’t published for that year, so totals here are a floor — the shortfall is largest in the sparse early years.