This study investigated the effect of integrating clinical data with DCE-MRI texture features in early prediction of breast cancer therapy response. DCE-MRI data collected from 55 breast cancer patients before and after the first cycle of neoadjuvant chemotherapy were subjected to pharmacokinetic analysis. Texture features were extracted from voxel-based DCE-MRI parametric maps. Predictive performances with imaging features alone and in combination with clinical features were assessed and compared. Addition of clinical features to image texture features increased predictive capability in discriminating pathologic complete response (pCR) vs. non-pCR compared to using imaging features alone.