Most Popular Baby Names In Kansas
The 100 most-used girls' and boys' names among recorded births from Kansas, 2016–2025 — 259,341 applications in that window. Below them: the names Kansas uses far more than the rest of the country.
Girls’ names
- 1Olivia1,6871.4%
- 2Charlotte1,5461.3%
- 3Emma1,4671.2%
- 4Amelia1,2351.0%
- 5Evelyn1,2211.0%
- 6Sophia1,1421.0%
- 7Harper1,1351.0%
- 8Ava1,0560.9%
- 9Eleanor9480.8%
- 10Isabella9270.8%
- 11Elizabeth9010.8%
- 12Mia8910.8%
- 13Avery7780.7%
- 14Abigail7680.7%
- 15Nora7530.6%
- 16Hazel7400.6%
- 17Scarlett6800.6%
- 18Ella6740.6%
- 19Ellie6450.5%
- 20Aurora6440.5%
- 21Violet6410.5%
- 22Grace6330.5%
- 23Lucy6200.5%
- 24Emily6010.5%
- 25Penelope6010.5%
- 26Luna5880.5%
- 27Sofia5810.5%
- 28Willow5800.5%
- 29Lillian5770.5%
- 30Paisley5770.5%
- 31Chloe5600.5%
- 32Zoey5490.5%
- 33Layla5480.5%
- 34Lily5430.5%
- 35Stella5410.5%
- 36Camila5200.4%
- 37Natalie5170.4%
- 38Claire5130.4%
- 39Aria5120.4%
- 40Hannah5090.4%
- 41Hadley4970.4%
- 42Addison4940.4%
- 43Josephine4890.4%
- 44Everly4830.4%
- 45Mila4830.4%
- 46Madison4690.4%
- 47Lydia4610.4%
- 48Emery4600.4%
- 49Isla4560.4%
- 50Ruby4510.4%
- 51Nova4480.4%
- 52Riley4460.4%
- 53Ivy4410.4%
- 54Kinsley4400.4%
- 55Naomi4220.4%
- 56Cora4200.4%
- 57Kennedy4160.4%
- 58Gianna4090.3%
- 59Brooklyn4040.3%
- 60Vivian4040.3%
- 61Sadie4020.3%
- 62Clara4000.3%
- 63Quinn4000.3%
- 64Eliana3950.3%
- 65Victoria3940.3%
- 66Anna3870.3%
- 67Caroline3840.3%
- 68Piper3800.3%
- 69Adeline3780.3%
- 70Zoe3710.3%
- 71Audrey3670.3%
- 72Elena3580.3%
- 73Madelyn3570.3%
- 74Lainey3540.3%
- 75Emilia3500.3%
- 76Parker3410.3%
- 77Rylee3410.3%
- 78Josie3390.3%
- 79Leah3390.3%
- 80Alice3370.3%
- 81Delilah3370.3%
- 82Iris3250.3%
- 83Margaret3250.3%
- 84Sophie3210.3%
- 85Emersyn3190.3%
- 86Savannah3170.3%
- 87Autumn3150.3%
- 88Mary3130.3%
- 89Blakely2990.3%
- 90Ember2990.3%
- 91Raelynn2970.3%
- 92Eloise2960.3%
- 93Adalynn2950.3%
- 94Lyla2950.3%
- 95Eden2920.2%
- 96Maya2890.2%
- 97Brynlee2880.2%
- 98Maria2840.2%
- 99Allison2830.2%
- 100Gabriella2830.2%
Boys’ names
- 1Liam1,7351.2%
- 2Oliver1,6781.2%
- 3Henry1,5421.1%
- 4Noah1,4561.0%
- 5William1,3370.9%
- 6James1,3330.9%
- 7Theodore1,2740.9%
- 8Elijah1,1870.8%
- 9Benjamin1,1790.8%
- 10Hudson1,1300.8%
- 11Wyatt1,0450.7%
- 12Owen1,0350.7%
- 13Jackson1,0320.7%
- 14Jack9790.7%
- 15Lucas9590.7%
- 16Mason9380.7%
- 17Samuel9300.7%
- 18Grayson9230.7%
- 19Lincoln9200.6%
- 20Alexander8840.6%
- 21Asher8830.6%
- 22Levi8470.6%
- 23Daniel8430.6%
- 24Carter8340.6%
- 25Luke8320.6%
- 26Mateo8240.6%
- 27John8120.6%
- 28Logan8100.6%
- 29Michael8080.6%
- 30Cooper8030.6%
- 31Leo8030.6%
- 32Maverick7850.6%
- 33Ezra7770.5%
- 34Joseph7600.5%
- 35Gabriel7550.5%
- 36Isaac7540.5%
- 37Thomas7490.5%
- 38Sebastian7380.5%
- 39Brooks7260.5%
- 40Ethan7230.5%
- 41Bennett7080.5%
- 42Jacob7040.5%
- 43Charles7000.5%
- 44Easton6960.5%
- 45Miles6890.5%
- 46Aiden6490.5%
- 47Elias6490.5%
- 48Julian6380.5%
- 49David6350.4%
- 50Beau5990.4%
- 51Everett5960.4%
- 52Eli5820.4%
- 53Hunter5780.4%
- 54Weston5780.4%
- 55Matthew5770.4%
- 56Jaxon5650.4%
- 57Waylon5570.4%
- 58Ezekiel5410.4%
- 59Anthony5360.4%
- 60Andrew5270.4%
- 61Nolan5270.4%
- 62Isaiah5260.4%
- 63Silas5200.4%
- 64Wesley5140.4%
- 65Greyson5110.4%
- 66Caleb5100.4%
- 67Santiago4880.3%
- 68Rhett4860.3%
- 69Rowan4830.3%
- 70Ryker4830.3%
- 71Landon4820.3%
- 72Parker4790.3%
- 73Joshua4740.3%
- 74Jameson4720.3%
- 75Dylan4690.3%
- 76Emmett4690.3%
- 77Josiah4650.3%
- 78Roman4630.3%
- 79Graham4580.3%
- 80Adrian4510.3%
- 81Colton4480.3%
- 82Jonathan4400.3%
- 83Christopher4360.3%
- 84Christian4340.3%
- 85Declan4320.3%
- 86Jace4320.3%
- 87Carson4300.3%
- 88Harrison4200.3%
- 89Angel4140.3%
- 90Beckett4140.3%
- 91Axel4130.3%
- 92Connor4130.3%
- 93Cameron4080.3%
- 94Sawyer4080.3%
- 95Braxton3950.3%
- 96Bentley3940.3%
- 97Robert3940.3%
- 98Archer3910.3%
- 99Calvin3880.3%
- 100Jayden3850.3%
Kansas's signature names
Names used at least 2× as often in Kansas as across all states combined, 2016–2025. The multiple compares Kansas's share of listed births with the same share pooled across every state — the closest thing to "how Kansas does it differently" the data can support.
Girls’ names
- Berkley3.5× · 77 recorded
- Baylor3.5× · 72 recorded
- Kimber3.4× · 111 recorded
- Landry3.3× · 71 recorded
- Briar3.1× · 134 recorded
- Bristol3× · 151 recorded
- Wrenley2.9× · 193 recorded
- Collins2.8× · 219 recorded
- Maren2.8× · 132 recorded
- Halle2.8× · 81 recorded
- Hattie2.7× · 167 recorded
- Sutton2.6× · 237 recorded
- Remington2.6× · 167 recorded
- Sloan2.5× · 92 recorded
- Coraline2.5× · 88 recorded
- Kynlee2.5× · 63 recorded
- Hadlee2.5× · 61 recorded
- Drew2.5× · 53 recorded
- Aspen2.4× · 258 recorded
- Palmer2.4× · 165 recorded
- Adley2.4× · 90 recorded
- Karsyn2.4× · 90 recorded
- Murphy2.4× · 67 recorded
- Ensley2.4× · 62 recorded
- Wrenlee2.4× · 58 recorded
Boys’ names
- Brecken4.7× · 95 recorded
- Mccoy4× · 67 recorded
- Benedict3.7× · 55 recorded
- Landry3.6× · 57 recorded
- Baker3.5× · 210 recorded
- Riggs3.2× · 61 recorded
- Adler3.1× · 50 recorded
- Blaine2.9× · 54 recorded
- Tripp2.8× · 133 recorded
- Sutton2.7× · 124 recorded
- Banks2.6× · 118 recorded
- Huxley2.6× · 87 recorded
- Bowen2.5× · 194 recorded
- Bo2.5× · 121 recorded
- Boston2.5× · 91 recorded
- Augustine2.5× · 84 recorded
- Axton2.5× · 82 recorded
- Creed2.5× · 66 recorded
- Rhett2.4× · 486 recorded
- Hayes2.4× · 323 recorded
- Wade2.4× · 207 recorded
- Baylor2.4× · 134 recorded
- Ridge2.4× · 92 recorded
- Layton2.4× · 85 recorded
- Caspian2.4× · 69 recorded
All-time favorites, 1910–2025
The most-used names across everything Kansas has recorded since 1910 — a very different list, dominated by the high-birth, low-variety decades of the mid-century.
Girls’ names
- 1Mary43,3902.6%
- 2Linda17,4651.0%
- 3Betty16,9361.0%
- 4Patricia16,7711.0%
- 5Barbara15,3550.9%
- 6Jennifer14,8550.9%
- 7Elizabeth14,7070.9%
- 8Dorothy14,0770.8%
- 9Margaret12,4890.7%
- 10Helen11,9350.7%
- 11Karen11,7230.7%
- 12Donna11,6730.7%
- 13Susan10,9020.7%
- 14Carol10,7770.6%
- 15Nancy10,7590.6%
- 16Sarah10,6280.6%
- 17Ruth10,4200.6%
- 18Jessica10,3310.6%
- 19Sharon10,0220.6%
- 20Virginia9,5830.6%
- 21Shirley9,3790.6%
- 22Rebecca9,2320.6%
- 23Michelle9,0890.5%
- 24Lisa9,0340.5%
- 25Kimberly8,7820.5%
- 26Ashley8,7740.5%
- 27Debra8,6900.5%
- 28Emily8,6140.5%
- 29Amy8,5570.5%
- 30Sandra8,4080.5%
- 31Anna8,2100.5%
- 32Amanda8,0980.5%
- 33Angela8,0140.5%
- 34Janet7,8530.5%
- 35Cynthia7,8210.5%
- 36Melissa7,5120.4%
- 37Pamela7,4790.4%
- 38Emma7,2810.4%
- 39Laura7,2550.4%
- 40Stephanie7,2390.4%
- 41Evelyn7,1730.4%
- 42Brenda7,1520.4%
- 43Deborah6,9270.4%
- 44Joyce6,9090.4%
- 45Julie6,7950.4%
- 46Doris6,6780.4%
- 47Carolyn6,6650.4%
- 48Marilyn6,5960.4%
- 49Katherine6,5850.4%
- 50Connie6,3470.4%
Boys’ names
- 1Robert51,5822.8%
- 2John48,0772.6%
- 3James47,7242.6%
- 4Michael42,0592.3%
- 5William37,8652.0%
- 6David37,4922.0%
- 7Richard28,2471.5%
- 8Charles27,9991.5%
- 9Donald22,4391.2%
- 10Christopher18,5831.0%
- 11Thomas18,0211.0%
- 12Kenneth17,5810.9%
- 13Joseph17,1540.9%
- 14Daniel16,6970.9%
- 15Steven16,5410.9%
- 16Larry16,4240.9%
- 17Mark16,2950.9%
- 18Matthew16,0970.9%
- 19Gary15,0740.8%
- 20Ronald13,9670.8%
- 21Paul13,8930.7%
- 22Joshua13,1620.7%
- 23George12,7040.7%
- 24Brian12,2930.7%
- 25Andrew12,2170.7%
- 26Kevin11,9410.6%
- 27Jack11,6880.6%
- 28Jason11,5490.6%
- 29Jacob11,4220.6%
- 30Timothy10,9750.6%
- 31Ryan10,2180.5%
- 32Harold10,2030.5%
- 33Jeffrey9,8930.5%
- 34Jerry9,4700.5%
- 35Anthony9,4540.5%
- 36Scott9,2620.5%
- 37Edward9,2230.5%
- 38Raymond8,7460.5%
- 39Justin8,6400.5%
- 40Eric8,4830.5%
- 41Dennis8,4530.5%
- 42Stephen8,2890.4%
- 43Brandon8,2420.4%
- 44Benjamin7,9900.4%
- 45Aaron7,8520.4%
- 46Nicholas7,7300.4%
- 47Samuel7,6870.4%
- 48Tyler7,6580.4%
- 49Terry7,5820.4%
- 50Gregory7,4560.4%
State data starts in 1910 (national data goes back to 1880) and is censored per state and year: a name needs 5 uses in Kansas 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.