Milk production is one of the most important characteristics of dairy sheep and the identification of genes affecting milk production traits is critical to understand its genetics and to improve milk production in future generations. Three statistical techniques, namely genome-wide association study (GWAS), ridge-regression BLUP and BayesCπ, were used to identify SNPs in significant association with three milk production traits (milk yield, fat yield, and protein yield) in a crossbred dairy sheep population. The results suggested that chromosomes 1, 3, 4, 5, 7 and 11 were likely to harbor genes important to milk production because these chromosomes had the highest top-100-SNP variance contributions on the three milk production traits. The GWAS analysis identified between 74 and 288 genome-wide significant SNP (P < 0.05) whereas the BayesCπ model showed 6 and 63 SNPs each with > 95% posterior probability of inclusion as SNPs having non-zero association effects on each of the three milk production traits. A validation-by-location search was conducted in the animalQTLDB, which showed that 27 chromosomal regions coincided with the findings of previous studies. These SNPs support previous findings and add new information about genetic markers for genetic improvement of lactation in dairy sheep.