Abstract Background: The extent to which common genetic variation can assist in breast cancer (BCa) risk assessment is unclear. We assessed the addition of risk information from a panel of BCa-associated single nucleotide polymorphisms (SNPs) on risk stratification offered by the Gail Model.Methods: We selected 7 validated SNPs from the literature and genotyped them among white women in a nested case-control study within the Women’s Health Initiative Clinical Trial. To model SNP risk, previously published odds ratios were combined multiplicatively. To produce a combined clinical/genetic risk, Gail Model risk estimates were multiplied by combined SNP odds ratios. We assessed classification performance using reclassification tables and receiver operating characteristic (ROC) curves. Results: The SNP risk score was well calibrated and nearly independent of Gail risk, and the combined predictor was more predictive than either Gail risk or SNP risk alone. In ROC curve analysis, the combined score had an area under the curve (AUC) of 0.594 compared to 0.557 for Gail risk alone. For reclassification with 5-year risk thresholds at 1.5% and 2%, the net reclassification index (NRI) was 0.085 (Z = 4.3, P = 1.0 × 10^-5^). Focusing on women with Gail 5-year risk of 1.5-2% results in an NRI of 0.195 (Z = 3.8, P = 8.6 × 10^−5^). Conclusions: Combining clinical risk factors and validated common genetic risk factors results in improvement in classification of BCa risks in white, postmenopausal women. This may have implications for informing primary prevention and/or screening strategies. Future research should assess the clinical utility of such strategies.