A total of 200 patients receiving both DCE-MRI and mammography were analyzed, including 146 malignant and 56 benign lesions. For each lesion, 3D tumor mask was done using fuzzy-C-means clustering algorithm. Three DCE parametric maps were generated, and the radiomics features were extracted from these maps by PyRadiomics. Five models were built based on DCE-MRI, mammography, and the combination. The BI-RADS score was obtained from the radiology reports for comparison. The model built based on all MRI and mammography features yielded the highest accuracy of 89.6%, and had significantly better diagnostic performance than BI-RADS using threshold of 4A or 4B.