Top 100 Most Popular U.S. Baby Names Of 1954

Page of 2

1954 Popular Names U.S. - Top 100 Baby Names
				Change from 1953						Change from 1953
Girls		Number of Girls	%	Rank	Number	Boys		Number of Boys	%	Rank	Number
1	Mary	68,007	3.416	0	3,628	1	Michael	88,528	4.280	2	4,302
2	Linda	55,381	2.782	0	-5,899	2	Robert	86,298	4.172	-1	42
3	Deborah	54,677	2.747	0	2,476	3	James	86,272	4.171	-1	173
4	Patricia	49,146	2.469	0	-1,872	4	John	81,165	3.924	0	975
5	Susan	47,151	2.368	0	2,854	5	David	79,529	3.845	0	3,377
6	Debra	45,890	2.305	1	9,030	6	William	61,417	2.969	0	-423
7	Barbara	36,370	1.827	-1	-2,102	7	Richard	57,014	2.756	0	-1,389
8	Karen	32,454	1.630	1	2,601	8	Thomas	47,158	2.280	0	153
9	Nancy	30,264	1.520	-1	-354	9	Gary	37,919	1.833	1	947
10	Cynthia	27,616	1.387	2	2,484	10	Charles	37,451	1.811	-1	-983
11	Donna	27,428	1.378	2	3,199	11	Steven	36,614	1.770	0	2,892
12	Pamela	27,365	1.375	-2	1,606	12	Mark	36,193	1.750	0	6,842
13	Sandra	26,061	1.309	-2	563	13	Joseph	31,211	1.509	0	1,939
14	Kathleen	22,459	1.128	0	-1,275	14	Donald	29,263	1.415	0	903
15	Carol	22,245	1.117	1	-50	15	Ronald	27,604	1.335	0	-120
16	Sharon	22,210	1.116	-1	-836	16	Paul	26,218	1.268	1	708
17	Diane	22,050	1.108	0	702	17	Kenneth	26,167	1.265	-1	645
18	Brenda	19,602	0.985	0	-531	18	Daniel	25,262	1.221	2	1,757
19	Janet	18,470	0.928	0	697	19	Larry	24,599	1.189	-1	-617
20	Elizabeth	16,580	0.833	1	481	20	Stephen	21,874	1.057	1	55
21	Margaret	15,228	0.765	-1	-972	21	Dennis	20,751	1.003	-2	-2,908
22	Cheryl	15,013	0.754	6	2,745	22	Edward	19,515	0.943	1	530
23	Kathy	14,169	0.712	0	771	23	Jeffrey	19,057	0.921	2	3,114
24	Denise	13,716	0.689	7	1,769	24	George	18,687	0.903	-2	-501
25	Janice	13,513	0.679	-3	-1,111	25	Gregory	17,615	0.852	-1	1,452
26	Rebecca	13,210	0.664	-2	249	26	Timothy	17,428	0.843	0	2,237
27	Carolyn	12,153	0.610	-2	-765	27	Terry	15,552	0.752	3	2,297
28	Joyce	12,088	0.607	-2	-710	28	Kevin	15,320	0.741	8	5,306
29	Judy	11,633	0.584	-2	-1,100	29	Douglas	14,702	0.711	-2	559
30	Judith	11,197	0.562	0	-770	30	Bruce	14,142	0.684	-2	96
31	Beverly	11,160	0.561	3	-77	31	Jerry	13,666	0.661	-2	-245
32	Catherine	11,077	0.556	3	231	32	Anthony	13,127	0.635	0	1,429
33	Shirley	10,910	0.548	-4	-1,236	33	Randy	12,628	0.611	2	1,954
34	Teresa	10,840	0.545	8	1,906	34	Roger	11,715	0.566	-3	-1,460
35	Marilyn	10,811	0.543	1	70	35	Raymond	11,237	0.543	-1	113
36	Betty	10,616	0.533	-3	-754	36	Frank	10,992	0.531	-3	-189
37	Gail	9,724	0.488	2	138	37	Peter	10,082	0.487	1	349
38	Paula	9,688	0.487	2	133	38	Patrick	9,922	0.480	1	450
39	Connie	9,633	0.484	8	1,056	39	Lawrence	9,599	0.464	-2	-257
40	Joan	9,518	0.478	-3	-256	40	Scott	9,454	0.457	6	1,962
41	Robin	9,043	0.454	25	3,002	41	Wayne	9,169	0.443	-1	260
42	Gloria	8,920	0.448	-4	-758	42	Danny	9,099	0.440	-1	472
43	Christine	8,787	0.441	-11	-3,009	43	Alan	8,709	0.421	0	255
44	Ann	8,753	0.440	2	176	44	Gerald	8,543	0.413	-2	-79
45	Laura	8,717	0.438	6	1,085	45	Keith	8,360	0.404	2	982
46	Martha	8,596	0.432	-5	-665	46	Ricky	8,157	0.394	5	1,267
47	Theresa	8,509	0.427	3	792	47	Carl	8,135	0.393	-3	306
48	Peggy	8,456	0.425	-4	-304	48	Brian	8,074	0.390	5	1,406
49	Jane	8,347	0.419	-6	-563	49	Walter	7,477	0.361	-4	-37
50	Vicki	8,221	0.413	11	1,397	50	Dale	7,443	0.360	-2	99

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.