Abstract Hanwoo is one of the indigenous cattle breeds in South Korea, and genetic evaluation at the national level is conducted using custom Illumina SNP arrays. Accurate gender assignment is essential in genetic evaluation and breeding programs for livestock species. In this study, we described a method for using custom single nucleotide polymorphism (SNP) array data to predict gender of Hanwoo cattle using logistic regression model. We analyzed a set of 958 SNPs, with 947 located on the X chromosome and 11 on the Y chromosome, focusing on heterozygosity rates from the X chromosome and missing rates from Y chromosome SNPs. Using a training dataset comprising 5,000 bulls and 2,005 cows with accurately recorded genders, we built a prediction model. Subsequently, we evaluated the performance of the model on test datasets consisting of 6,657 bulls, 27 steers, and 8,418 cows. The concordance between predicted gender and recorded gender were 99.98%, 100.00% and 99.98% for bulls, steers, and cows, respectively. This result showed better accuracy of gender prediction compared with the GENOMESTUDIO tool that uses only the heterozygosity rate of SNPs in X chromosome in the case of restricted number of SNPs in sex chromosomes. Overall, our findings could be used as an effective method for more precise genetic evaluation by correcting potential gender errors in Hanwoo cattle breeding programs.