Objective Carotid endarterectomy (CEA) has been shown to be an effective treatment for patients with asymptomatic carotid artery stenosis when perioperative stroke rates are low and patients survive long enough to benefit from the intervention. Our objective was to develop and to validate a simple risk prediction model for 30-day stroke and 1-year mortality to guide optimal selection of patients for CEA. Methods Asymptomatic patients undergoing first-time elective CEA within the Vascular Quality Initiative (VQI) from 2010 to 2015 were selected. Outcome measures included any 30-day postoperative stroke and 1-year mortality. Patient demographics, comorbidities, carotid artery disease burden, and provider characteristics were evaluated to select a parsimonious clinical model for risk prediction using multivariable logistic regression. Internal validation was performed for stroke and split sample validation was done for 1-year survival to ensure generalizability. Results We identified 31,939 patients for inclusion in the stroke analysis (2010-2015) and 24,086 patients for the mortality analysis (2010-2014). Both the 30-day stroke rate (0.9%) and 1-year mortality rate (3.4%) varied substantially across 265 VQI centers (range, 0%-8.3% and 0%-20%, respectively). Eleven significant factors were selected for the 30-day stroke risk prediction model (area under the receiver operating characteristic curve [AUC], 0.67). Internal validation demonstrated good discrimination (bias corrected AUC = 0.652; calibration intercept and slope of 0.03 and 1.01, respectively). Similarly, 10 significant factors were selected for the 1-year mortality risk prediction model (AUC, 0.764). External validation demonstrated excellent discrimination and calibration (AUC, 0.764; 95% confidence interval, 0.72-0.80). Conclusions Stroke and 1-year mortality rates after CEA for asymptomatic stenosis vary across VQI centers. We have developed a preoperative risk model that can be used to accurately estimate risk of perioperative stroke and 1-year mortality and to assist providers in selecting patients with asymptomatic stenosis who are most likely to benefit from CEA.