The implementation of genomic selection for Japanese Black cattle, known for rich marbling of their meat, is now being explored. Although multiple-step methods are often adopted for dairy cattle, they present shortcomings such as bias and loss of information in addition to operational complexity. These can be avoided using single-step genomic BLUP (ssGBLUP) based on the relationship matrix H, which is constructed from the numerator relationship matrix (A) augmented by the genomic relationship matrix (G). This study assessed the use of ssGBLUP for 3 economically important traits in Japanese Black cattle. Three aspects of ssGBLUP that are important for practical use were examined specifically: the mixing proportions of blending G with A, selection of subsets of genotyped animals used for constructing H, and prediction ability for ungenotyped animals. Different mixing proportions were tested to assess the influence of these proportions on variance component estimation and prediction accuracy. For all traits, the highest or nearly highest accuracy was obtained when the adopted mixing proportion provided heritability closest to that inferred based on A. However, the accuracy did not increase greatly under adjustment of the mixing proportion, thereby suggesting that the influence of the mixing proportion on the accuracy was limited. Genotype data of influential bulls showed a greater contribution to accuracy than that of bulls that were less influential. Genotyping animals with phenotypic records increased the accuracy. It can be prioritized over genotyping bulls that are not influential on the population. These results are expected to present good guides to the future expansion of genotyped populations. Even for animals without genotype data but with genotyped sires, ssGBLUP provided more accurate prediction than BLUP did. For both phenotype and breeding value prediction, ssGBLUP provides more accurate prediction than BLUP, suggesting its usefulness in genomic selection in Japanese Black cattle.