In this study, we used magnetic resonance (MR)-based clinical and radiomic features to assess tumor heterogeneity in 311 HER2 overexpressing breast cancer patients receiving neoadjuvant chemotherapy (NAC), and correlated these findings with tumor heterogeneity and pathologic response. Tumor heterogeneity was evaluated based on the HER2 expression (IHC vs. FISH) . Pathologic complete response (pCR) was defined as no residual invasive carcinoma in the breast or axillary lymph nodes (ypT0/isN0). Radiomics analysis and machine learning with MRI were able to assess tumor heterogeneity and predict pCR after neoadjuvant chemotherapy in these patients, with a diagnostic accuracy of 97.4% and 85.2%, respectively.