With 1 in 8 women in the United States at risk of developing breast cancer at some point in their lifetime, the development and accuracy of breast cancer risk assessment models is pertinent. As a partner with the Athena Breast Health Network, an extensive program at UCI that drives innovation in the prevention of breast cancer, this study was interested in determining which model(s) of the Gail, BCSC, and Tyrer-Cuzick models are the best breast cancer risk assessments for each ethnicity. Utilizing data from the Athena study, an online comprehensive assessment of race/ethnicity, date of birth, and other risk factors associated with breast cancer, a computational program was created to automate the reporting of breast cancer risk scores for women participating in the Athena research program. The sensitivity and specificity of the models for breast cancer risk in the Athena research program were then used to evaluate their predictive accuracies. Finally, the risk assessment scores data were examined to determine correlations between different patient characteristics such as races/ethnicities.