Despite improved detection and reduction of breast cancer-related deaths over the recent decade, breast cancer remains the second leading cause of cancer death for women in the US, with 39,510 women expected to succumb to metastatic disease in 2012 alone (American Cancer Society, Cancer Facts &Figures 2012. Atlanta: American Cancer Society; 2012). Continued efforts in classification of breast cancers based on gene expression profiling and genomic sequencing have revealed an underlying complexity and molecular heterogeneity within the disease that continues to challenge therapeutic interventions. To successfully identify and translate new treatment regimens to the clinic, it is imperative that our preclinical models recapitulate this complexity and heterogeneity. In this review article, we discuss the recent advances in development and classification of patient-derived human breast tumor xenograft models that have the potential to facilitate the next phase of drug discovery for personalized cancer therapy based on the unique driver signaling pathways in breast tumor subtypes.