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The data reported here have been supplied in part by the U.S. Renal Data System. Support for the Department of Veterans Affairs/Centers for Medicare and Medicaid Services data is provided by the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Health Services Research and Development, and Veterans Affairs Information Resource Center (project numbers SDR 02-237 and 98-004). Dr Kalantar-Zadeh is supported by National Institute of Diabetes and Digestive and Kidney Diseases grant K24-DK091419 as well as philanthropic grants from Mr Harold Simmons, Mr Louis Chang, and Dr Joseph Lee. Dr Obi is supported by the Uehara Memorial Foundation Research Fellowship. Dr Rhee is supported by grants K23-DK102903 and R03-DK114642 from the National Institute of Diabetes and Digestive and Kidney Diseases. Dr Streja is supported by Department of Veterans Affairs grant IK2-CX001266-001. 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Patients and Methods: We developed a risk prediction tool for mortality during the first year of dialysis based on pre-end-stage renal disease characteristics in a cohort of 35,878 US veterans with incident end-stage renal disease who transitioned to dialysis treatment between October 1, 2007, and March 31, 2014 and then externally validated this tool among 4284 patients in the Kaiser Permanente Southern California (KPSC) health care system who transitioned to dialysis treatment between January 1, 2007, and September 30, 2015. Results: To ensure model goodness of fit, 2 separate models were selected for patients whose last estimated glomerular filtration rate (eGFR) before dialysis initiation was less than 15 mL/min per 1.73 m(2) or 15 mL/min per 1.73 m(2) or higher. Model discrimination in the internal validation cohort of veterans resulted in C statistics of 0.71 (95% CI, 0.70-0.72) and 0.66 (95% CI, 0.65-0.67) among patients with eGFR lower than 15 mL/min per 1.73 m(2) and 15 mL/min per 1.73 m(2) or higher, respectively. In the KPSC external validation cohort, the developed risk score exhibited C statistics of 0.77 (95% CI, 0.74-0.79) in men and 0.74 (95% CI, 0.71-0.76) in women with eGFR lower than 15 mL/min per 1.73 m(2) and 0.71 (95% CI, 0.67-0.74) in men and 0.67 (95% CI, 0.62-0.72) in women with eGFR of 15 mL/min per 1.73 m(2) or higher. Conclusion: A new risk prediction tool for mortality during the first year after transition to dialysis (available at www.DialysisScore.com) was developed in the large national Veterans Affairs cohort and validated with good performance in the racially, ethnically, and gender diverse KPSC cohort. This risk prediction tool will help identify high-risk populations and guide management strategies at the transition to dialysis. 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