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Numerous variants of unknown significance (VUSs) exist in hereditary breast and ovarian cancers. Although multiple methods have been developed to assess the significance of BRCA1/2variants, functional discrepancies among these approaches remain. Therefore, a comprehensive functional evaluation system for these variants should be established. We performed conventional homologous recombination (HR) assays for 50 BRCA1and 108 BRCA2VUSs and complementarily predicted VUSs using a statistical logistic regression prediction model that integrated six in silico functional prediction tools. BRCA1/2VUSs were classified according to the results of the integrative in vitro and in silico analyses. Using HR assays, we identified 10 BRCA1and 4 BRCA2VUSs as low-functional pathogenic variants. For in silico prediction, the statistical prediction model showed high accuracy for both BRCA1and BRCA2compared with each in silico prediction tool individually and predicted nine BRCA1and seven BRCA2variants to be pathogenic. Integrative functional evaluation in this study and the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines strongly suggested that seven BRCA1variants (p.Glu272Gly, p.Lys1095Glu, p.Val1653Leu, p.Thr1681Pro, p.Phe1761Val, p.Thr1773Ile, and p.Gly1803Ser) and four BRCA2variants (p.Trp31Gly, p.Ser2616Phe, p.Tyr2660Cys, and p.Leu2792Arg) were pathogenic. This study demonstrates that integrative evaluation using conventional HR assays and optimized in silico prediction comprehensively classified the significance of BRCAVUSs for future clinical applications.