BACKGROUND: The empirically derived 2014 Society of Thoracic Surgeons Congenital Heart Surgery Database Mortality Risk Model incorporates adjustment for procedure type and patient-specific factors. The purpose of this report is to describe this model and its application in the assessment of variation in outcomes across centers. METHODS: All index cardiac operations in The Society of Thoracic Surgeons Congenital Heart Surgery Database (January 1, 2010, to December 31, 2013) were eligible for inclusion. Isolated patent ductus arteriosus closures in patients weighing less than or equal to 2.5 kg were excluded, as were centers with more than 10% missing data and patients with missing data for key variables. The model includes the following covariates: primary procedure, age, any prior cardiovascular operation, any noncardiac abnormality, any chromosomal abnormality or syndrome, important preoperative factors (mechanical circulatory support, shock persisting at time of operation, mechanical ventilation, renal failure requiring dialysis or renal dysfunction (or both), and neurological deficit), any other preoperative factor, prematurity (neonates and infants), and weight (neonates and infants). Variation across centers was assessed. Centers for which the 95% confidence interval for the observed-to-expected mortality ratio does not include unity are identified as lower-performing or higher-performing programs with respect to operative mortality. RESULTS: Included were 52,224 operations from 86 centers. Overall discharge mortality was 3.7% (1,931 of 52,224). Discharge mortality by age category was neonates, 10.1% (1,129 of 11,144); infants, 3.0% (564 of 18,554), children, 0.9% (167 of 18,407), and adults, 1.7% (71 of 4,119). For all patients, 12 of 86 centers (14%) were lower-performing programs, 67 (78%) were not outliers, and 7 (8%) were higher-performing programs. CONCLUSIONS: The 2014 Society of Thoracic Surgeons Congenital Heart Surgery Database Mortality Risk Model facilitates description of outcomes (mortality) adjusted for procedural and for patient-level factors. Identification of low-performing and high-performing programs may be useful in facilitating quality improvement efforts.