A genome-wide association study (GWAS) was conducted on 15 milk production traits in Chinese Holstein. The experimental population consisted of 445 cattle, each genotyped by the GGP (GeneSeek genomic profiling)-BovineLD V3 SNP chip, which had 26,151 public SNPs on its manifest file. After data cleaning, 20,326 SNPs were retained for GWAS. The phenotypes were estimated breeding values of these traits, provided by a public Dairy-Herd Improvement (DHI) program center which has been conducted once a month for three years. Two statistical models, a fixed-effect linear regression model (FLM) and a mixed-effect linear model (MLM), were used to estimate the association effects of SNPs on each of the phenotypes. Genome-wide significant and suggestive thresholds were set up to be 2.46E-06 and 4.95E-05, respectively. The two statistical models coincidedly identified two genome-wide significant (<5%) SNPs on milk production traits in this Chinese Holstein population. The positional candidate genes, which were the ones closest to these two identified SNPs were EEF2K (eukaryotic elongation factor 2 kinase) and KLHL1 (kelch-like family member 1). These two genes can serve as new candidate genes for milk yield and lactation persistence, yet their roles need to be verified in further function studies.