Top 1000 Most Popular U.S. Baby Names Of 1949

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1949 Popular Names U.S. - Top 1000 Baby Names
				Change from 1948						Change from 1948
Girls		Number of Girls	%	Rank	Number	Boys		Number of Boys	%	Rank	Number
1	Linda	91,016	5.185	0	-5,195	1	James	86,857	4.820	0	-1,727
2	Mary	66,864	3.809	0	-1,733	2	Robert	83,872	4.655	0	-1,603
3	Patricia	46,330	2.639	1	194	3	John	81,161	4.504	0	-1,668
4	Barbara	42,601	2.427	-1	-4,225	4	William	61,501	3.413	0	-464
5	Susan	37,706	2.148	0	1,721	5	Michael	60,046	3.332	1	7,482
6	Sandra	30,642	1.745	0	-418	6	David	59,601	3.308	-1	2,978
7	Nancy	29,246	1.666	0	-165	7	Richard	50,939	2.827	0	-31
8	Carol	26,783	1.526	0	-2,196	8	Thomas	45,202	2.509	0	1,424
9	Kathleen	26,354	1.501	1	3,098	9	Charles	40,042	2.222	0	1,366
10	Sharon	25,711	1.465	-1	-431	10	Larry	31,809	1.765	1	-1,622
11	Karen	22,467	1.280	1	471	11	Ronald	31,492	1.748	-1	-2,026
12	Donna	22,057	1.256	-1	26	12	Gary	28,925	1.605	0	531
13	Brenda	20,544	1.170	4	2,848	13	Donald	27,113	1.505	1	670
14	Margaret	19,451	1.108	-1	577	14	Joseph	26,403	1.465	-1	-402
15	Deborah	19,209	1.094	15	7,965	15	Kenneth	23,585	1.309	0	34
16	Judith	17,610	1.003	-1	-178	16	Dennis	21,745	1.207	1	-13
17	Carolyn	17,405	0.991	-3	-1,214	17	Paul	21,585	1.198	1	335
18	Shirley	17,278	0.984	2	1,152	18	George	21,313	1.183	-2	-610
19	Diane	17,250	0.983	0	643	19	Stephen	20,481	1.137	1	3,422
20	Judy	15,981	0.910	-4	-1,721	20	Steven	19,921	1.106	3	3,940
21	Pamela	15,132	0.862	1	854	21	Edward	19,168	1.064	-2	191
22	Betty	14,942	0.851	-4	-1,680	22	Daniel	18,235	1.012	0	1,728
23	Janet	14,858	0.846	1	880	23	Jerry	15,868	0.881	-2	-939
24	Janice	14,452	0.823	-1	291	24	Mark	13,727	0.762	5	3,462
25	Elizabeth	13,712	0.781	1	500	25	Roger	12,821	0.712	-1	4
26	Joyce	13,571	0.773	-5	-810	26	Bruce	12,264	0.681	2	1,199
27	Cynthia	12,897	0.735	0	656	27	Frank	11,958	0.664	-2	-735
28	Cheryl	12,006	0.684	-3	-1,216	28	Terry	11,457	0.636	-2	-677
29	Gloria	11,877	0.677	-1	189	29	Douglas	11,323	0.628	4	1,854
30	Christine	11,797	0.672	5	2,118	30	Raymond	11,304	0.627	-3	-309
31	Beverly	10,555	0.601	0	-241	31	Gregory	10,980	0.609	1	1,257
32	Dorothy	10,407	0.593	-3	-917	32	Lawrence	10,252	0.569	-1	488
33	Marilyn	9,867	0.562	0	-68	33	Gerald	9,807	0.544	-3	-37
34	Martha	9,809	0.559	-2	-197	34	Timothy	9,342	0.518	4	1,302
35	Bonnie	9,730	0.554	-1	-87	35	Wayne	8,926	0.495	-1	245
36	Joan	9,205	0.524	1	-67	36	Anthony	8,452	0.469	5	572
37	Catherine	9,136	0.520	4	891	37	Walter	8,295	0.460	-2	-331
38	Peggy	9,119	0.519	0	31	38	Peter	8,263	0.459	-1	213
39	Virginia	8,894	0.507	-3	-404	39	Patrick	8,074	0.448	9	884
40	Rebecca	8,776	0.500	10	1,981	40	Danny	8,024	0.445	-1	20
41	Jane	8,719	0.497	-2	-61	41	Willie	7,913	0.439	-1	-56
42	Kathy	8,451	0.481	13	2,303	42	Harold	7,813	0.434	-6	-330
43	Connie	8,219	0.468	0	164	43	Carl	7,690	0.427	-1	-140
44	Ann	7,869	0.448	0	-156	44	Arthur	7,478	0.415	0	-104
45	Jean	7,760	0.442	2	-13	45	Alan	7,256	0.403	1	-138
46	Helen	7,707	0.439	-6	-595	46	Henry	7,179	0.398	-1	-242
47	Ruth	7,652	0.436	-2	-252	47	Jack	7,133	0.396	-4	-479
48	Diana	7,535	0.429	0	-168	48	Jeffrey	6,986	0.388	10	1,058
49	Frances	7,440	0.424	-7	-737	49	Johnny	6,969	0.387	3	110
50	Phyllis	7,314	0.417	-4	-562	50	Ralph	6,746	0.374	1	-166

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.