Top 1000 Most Popular U.S. Baby Names Of 1999

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1999 Popular Names U.S. - Top 1000 Baby Names
				Change from 1998						Change from 1998
Girls		Number of Girls	%	Rank	Number	Boys		Number of Boys	%	Rank	Number
1	Emily	26,539	1.364	0	357	1	Jacob	35,363	1.735	1	-653
2	Hannah	21,676	1.114	0	303	2	Michael	33,912	1.664	-1	-2,703
3	Alexis	19,234	0.988	3	-544	3	Matthew	30,415	1.492	0	-727
4	Sarah	19,104	0.982	0	-780	4	Joshua	27,258	1.337	0	-831
5	Samantha	19,038	0.978	-2	-1,154	5	Nicholas	25,638	1.258	1	-996
6	Ashley	18,136	0.932	-1	-1,737	6	Christopher	25,603	1.256	-1	-1,399
7	Madison	18,053	0.928	2	266	7	Andrew	23,855	1.170	2	197
8	Taylor	16,905	0.869	-1	-1,667	8	Joseph	23,213	1.139	3	32
9	Jessica	16,348	0.840	-1	-1,887	9	Daniel	22,694	1.113	3	-461
10	Elizabeth	15,345	0.788	0	158	10	Tyler	22,665	1.112	-2	-1,046
11	Alyssa	14,035	0.721	0	325	11	Brandon	21,599	1.060	-4	-2,230
12	Lauren	13,911	0.715	2	1,004	12	Ryan	21,013	1.031	5	818
13	Kayla	13,289	0.683	-1	-133	13	Austin	20,767	1.019	-3	-2,710
14	Brianna	12,414	0.638	3	367	14	William	20,710	1.016	0	-123
15	Megan	12,225	0.628	-2	-1,028	15	John	20,348	0.998	0	-279
16	Victoria	11,871	0.610	0	-276	16	David	20,340	0.998	-3	-545
17	Emma	11,730	0.603	5	1,288	17	Zachary	19,981	0.980	-1	-598
18	Abigail	11,681	0.600	0	583	18	Anthony	19,469	0.955	1	-162
19	Rachel	11,624	0.597	-4	-580	19	James	18,552	0.910	-1	-1,135
20	Olivia	11,254	0.578	1	644	20	Justin	18,276	0.897	0	305
21	Jennifer	10,614	0.545	-1	-77	21	Alexander	17,416	0.854	1	-48
22	Amanda	9,743	0.501	-3	-1,172	22	Jonathan	17,062	0.837	-1	-585
23	Sydney	9,648	0.496	5	1,097	23	Dylan	15,979	0.784	2	1,440
24	Morgan	9,606	0.494	-1	-611	24	Noah	14,923	0.732	5	1,514
25	Nicole	9,515	0.489	-1	-396	25	Christian	14,779	0.725	1	263
26	Jasmine	9,351	0.480	0	-133	26	Robert	14,539	0.713	-3	-985
27	Grace	9,179	0.472	27	3,460	27	Samuel	14,040	0.689	1	131
28	Destiny	9,173	0.471	6	1,020	28	Kyle	13,772	0.676	-4	-1,502
29	Anna	9,104	0.468	2	724	29	Benjamin	13,661	0.670	1	602
30	Julia	8,751	0.450	2	423	30	Jordan	13,051	0.640	-3	-1,357
31	Haley	8,202	0.421	5	267	31	Thomas	12,791	0.627	0	-94
32	Alexandra	8,164	0.419	-5	-441	32	Nathan	12,535	0.615	2	951
33	Kaitlyn	8,157	0.419	2	221	33	Cameron	12,435	0.610	2	1,018
34	Natalie	8,080	0.415	6	534	34	Kevin	12,256	0.601	-2	-251
35	Brittany	7,942	0.408	-10	-1,901	35	Jose	12,152	0.596	-2	-220
36	Katherine	7,934	0.408	-3	-270	36	Hunter	11,485	0.563	0	407
37	Stephanie	7,691	0.395	-8	-800	37	Ethan	11,443	0.561	1	910
38	Rebecca	7,429	0.382	-8	-991	38	Aaron	9,853	0.483	-1	-695
39	Maria	7,030	0.361	4	213	39	Eric	9,380	0.460	0	-583
40	Allison	7,025	0.361	-2	-836	40	Jason	9,363	0.459	0	-32
41	Amber	6,840	0.351	-4	-1,089	41	Caleb	9,279	0.455	1	251
42	Savannah	6,805	0.350	2	342	42	Logan	9,135	0.448	2	497
43	Danielle	6,752	0.347	-2	-616	43	Brian	8,807	0.432	-2	-336
44	Courtney	6,557	0.337	-5	-997	44	Adam	8,223	0.403	1	-134
45	Mary	6,374	0.327	0	-84	45	Cody	7,864	0.386	-2	-947
46	Gabrielle	6,130	0.315	1	-71	46	Juan	7,799	0.383	6	438
47	Brooke	6,067	0.312	-1	-277	47	Steven	7,689	0.377	-1	-425
48	Jordan	5,730	0.294	-6	-1,382	48	Connor	7,597	0.373	-1	-308
49	Sierra	5,713	0.294	2	-127	49	Timothy	7,592	0.372	0	-253
50	Sara	5,624	0.289	-2	-383	50	Charles	7,524	0.369	-2	-323

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.