Top 100 Most Popular U.S. Baby Names Of 2018

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2018 Popular Names U.S. - Top 100 Baby Names
				Change from 2017						Change from 2017
Girls		Number of Girls	%	Rank	Number	Boys		Number of Boys	%	Rank	Number
1	Emma	18,688	1.012	0	-1,112	1	Liam	19,837	1.028	0	1,039
2	Olivia	17,921	0.971	0	-782	2	Noah	18,267	0.947	0	-143
3	Ava	14,924	0.808	0	-1,034	3	William	14,516	0.753	0	-451
4	Isabella	14,464	0.783	0	-716	4	James	13,525	0.701	0	-766
5	Sophia	13,928	0.754	0	-955	5	Oliver	13,389	0.694	4	196
6	Charlotte	12,940	0.701	1	3	6	Benjamin	13,381	0.694	0	-416
7	Mia	12,642	0.685	-1	-828	7	Elijah	12,886	0.668	1	-458
8	Amelia	12,301	0.666	0	468	8	Lucas	12,585	0.652	3	-411
9	Harper	10,582	0.573	2	95	9	Mason	12,435	0.645	-2	-1,114
10	Evelyn	10,376	0.562	-1	-336	10	Logan	12,352	0.640	-5	-1,662
11	Abigail	9,796	0.531	-1	-811	11	Alexander	11,989	0.622	2	-530
12	Emily	8,656	0.469	0	-1,125	12	Ethan	11,854	0.615	2	-585
13	Elizabeth	8,513	0.461	0	-442	13	Jacob	11,770	0.610	-3	-1,408
14	Mila	8,126	0.440	16	2,162	14	Michael	11,620	0.602	-2	-1,019
15	Ella	8,055	0.436	1	9	15	Daniel	11,173	0.579	0	-518
16	Avery	8,053	0.436	-2	-152	16	Henry	10,649	0.552	2	188
17	Sofia	7,621	0.413	-2	-539	17	Jackson	10,323	0.535	3	-76
18	Camila	7,473	0.405	5	707	18	Sebastian	10,054	0.521	5	-118
19	Aria	7,394	0.401	1	245	19	Aiden	9,979	0.517	-2	-1,324
20	Scarlett	7,182	0.389	-2	-520	20	Matthew	9,924	0.515	-4	-1,747
21	Victoria	7,089	0.384	-2	-203	21	Samuel	9,734	0.505	0	-661
22	Madison	7,036	0.381	-5	-839	22	David	9,697	0.503	0	-490
23	Luna	6,897	0.374	14	1,553	23	Joseph	9,555	0.495	-4	-882
24	Grace	6,724	0.364	-3	-316	24	Carter	9,312	0.483	0	-475
25	Chloe	6,626	0.359	-3	-318	25	Owen	9,288	0.482	3	-50
26	Penelope	6,474	0.351	-2	-178	26	Wyatt	9,127	0.473	-1	-561
27	Layla	6,468	0.350	-1	165	27	John	9,119	0.473	0	-367
28	Riley	5,976	0.324	-3	-377	28	Jack	8,834	0.458	7	380
29	Zoey	5,899	0.320	0	-146	29	Luke	8,577	0.445	1	-618
30	Nora	5,799	0.314	-2	-256	30	Jayden	8,553	0.443	-4	-981
31	Lily	5,706	0.309	2	-131	31	Dylan	8,549	0.443	-2	-746
32	Eleanor	5,694	0.308	3	157	32	Grayson	8,538	0.443	2	-141
33	Hannah	5,629	0.305	-1	-278	33	Levi	8,440	0.438	4	22
34	Lillian	5,534	0.300	-7	-626	34	Isaac	8,417	0.436	-2	-434
35	Addison	5,203	0.282	-1	-413	35	Gabriel	8,335	0.432	-4	-796
36	Aubrey	5,190	0.281	-5	-721	36	Julian	8,307	0.431	0	-115
37	Ellie	5,190	0.281	7	185	37	Mateo	8,169	0.424	5	412
38	Stella	5,121	0.277	4	66	38	Anthony	8,003	0.415	-5	-830
39	Natalie	5,095	0.276	-3	-439	39	Jaxon	7,701	0.399	5	28
40	Zoe	5,062	0.274	1	-96	40	Lincoln	7,368	0.382	1	-811
41	Leah	4,995	0.271	-1	-180	41	Joshua	7,364	0.382	-2	-920
42	Hazel	4,916	0.266	1	-107	42	Christopher	7,261	0.376	-4	-1,024
43	Violet	4,794	0.260	4	75	43	Andrew	7,234	0.375	-3	-1,017
44	Aurora	4,785	0.259	7	194	44	Theodore	7,020	0.364	18	1,070
45	Savannah	4,745	0.257	-7	-493	45	Caleb	6,929	0.359	5	-196
46	Audrey	4,662	0.253	0	-163	46	Ryan	6,905	0.358	-3	-769
47	Brooklyn	4,611	0.250	-8	-575	47	Asher	6,802	0.353	12	772
48	Bella	4,518	0.245	2	-120	48	Nathan	6,790	0.352	-3	-628
49	Claire	4,379	0.237	0	-314	49	Thomas	6,779	0.351	0	-383
50	Skylar	4,378	0.237	-2	-340	50	Leo	6,719	0.348	11	769

United States name popularity data is provided by the Social Security Administration and is based on Social Security card applications.

Data for a given year is not made available until well into the next year.

Data reflects what was recorded and has not been edited for errors, so for example the gender associated with a name may be incorrect.

The more babies that are given a particular name, the higher the popularity ranking. If multiple names have the same usage, the tie is broken by assigning popularity rank in alphabetical order. Therefore in the case of names with fewer occurrences, names with the same number of occurrences may have vastly different rankings because they will be interranked alphabetically.

To safeguard privacy, the SSA does not include names with less than 5 occurrences.

Please note, we update the data each May when the SSA releases new figures. All data changes at that time, including previous years, which will change minutely based on new information.