The purpose of the study was to devise a method of stratifying open-heart operations into levels of predicted operative mortality, using objective data that are readily available in any hospital. Following univariate regression analysis of 3,500 consecutive operations, 14 risk factors were chosen that met these conditions. A few factors were excluded because they were insufficiently objective or not always available. An additive model was constructed, using the factors chosen, to calculate the probability of mortality within 30 days. The method was then tested prospectively in 1,332 open-heart procedures at the Newark Beth Israel Medical Center. Patients were categorized in five groups of increasing risk: good (0-4%), fair (5-9%), poor (10-14%), high (15-19%), and extremely high (greater than or equal to 20%). The correlation coefficient of anticipated and observed operative mortality, using the additive model, was 0.99. The operative mortality also correlated closely with complication rates and length of hospital stay. The additive model was compared with a second model based on logistic multiple regression; the resulting correlation coefficient was 0.85. The method was also tested at two other hospitals; although their sample sizes were smaller, the outcomes in each risk group were comparable with those at this institution. The collection of data proved to be acceptably simple for all three centers. This study demonstrates that it is possible to design a simple method of risk stratification of open-heart surgery patients that makes it feasible to analyze operative results by risk groups and to compare results in similar groups between institutions. Wider application of the system is recommended.