The Scientific Registry of Transplant Recipients is charged with providing program-specific reports for organ transplant programs in the United States. Monitoring graft survival for pancreas transplant programs has been problematic as there are three different pancreas transplant procedures that may have different outcomes, and analyzing them separately reduces events and statistical power. We combined two consecutive 2.5-year cohorts of transplant recipients to develop Cox proportional hazards models predicting outcomes, and tested these models in the second 2.5-year cohort. We used separate models for 1- and 3-year graft and patient survival for each transplant type: simultaneous pancreas–kidney (SPK), pancreas after kidney (PAK) and pancreas transplant alone (PTA). We first built a predictive model for each pancreas transplant type, and then pooled the transplant types within centers to compare total observed events with total predicted events. Models for 1-year pancreas graft and patient survival yielded C statistics of 0.65 (95% confidence interval, 0.63–0.68) and 0.66 (0.61–0.72), respectively, comparable to C statistics for 1-year patient and graft survival for other organ transplants. Model calibration (Hosmer–Lemeshow method) was also acceptable. We conclude that pooling the results of SPK, PAK and PTA can produce potentially useful models for reporting program-specific pancreas transplant outcomes.