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Chinese Simmental cattle serve as economically important dual-purpose animals, yet their milk production genetics under temperate conditions remain poorly characterized. Using 17,556 test-day records (1,788 cows; parities 1-3) and whole-genome sequences from 781 individuals, we applied random regression test-day models with Legendre polynomials to estimate variance components, heritabilities (range: 0.09 for fat-to-protein ratio to 0.52 for protein percentage), breeding values, and genetic correlations. Genome-wide association analysis and Bayesian fine-mapping analysis identified significant SNPs near known candidate genes (BOP1, MROH1,NEGR1). These analyses also revealed putative novel associations with CACNB4, MTHFD2L, and SGMS1. This work elucidates genetic regulation of milk synthesis and provides actionable markers for genomic selection, advancing dual-purpose Simmental breeding programs.