Despite the acute shortage of cadaveric organs for kidney transplantation, more than 10% of cadaveric kidneys are discarded each year because of marginal quality. Transplant recipients’ access to these kidneys and to information about their quality is limited. A Monte Carlo model was developed to simulate the operations of an organ procurement organization over a 10-yr period. Donor and recipient characteristics were generated from the United States Renal Data System. Kidneys were assigned one of five possible grades, which were determined by calculating the relative risk of graft failure associated with donor characteristics and HLA matching for every donor-candidate pair. Modeled were recipient decisions to accept or reject a kidney on the basis of the relative change in quality-adjusted life years (QALY). Compared were the United Network of Organ Sharing (UNOS) policy, the UNOS expanded donor criteria policy, two benchmark policies (one equity driven and the other efficiency driven), and a hybrid policy that incorporated recipient choice into the UNOS algorithm. Sensitivity analyses for major input variables were performed. Compared with UNOS, an algorithm that incorporated recipient choice predicted a 6% increase in QALY, a 12% decrease in median waiting time, a 39% increase in the likelihood of transplantation, and a 56% reduction in the number of discarded kidneys. Benefits were observed across categories of age, gender, and race. Incorporating recipient choice in kidney transplantation would improve equity, efficiency, and QALY of the end-stage renal disease population.