In this work, we looked at the significance of the race factor in breast cancer prognosis, using Association rules data mining technique. We utilized XLMiner data mining tool for our experiments. The data used is the National Cancer Institute’s SEER Public-Use Data. Several experiments were conducted based on the prognostic factors including those of Age, Behavior code, Stage of cancer, Grade, and Marital status with respect to Race. Our discovered association rules indicate that Japanese patients have better survival rate than White patients and White patients have better survival rate than Black patients. The racial disparity in breast cancer prognosis is shown to be statistically significant.