An index for prediction of outcome for use as a measure of the severity of illness was developed by a nonparametric multivariate analysis of cardiorespiratory data from 113 critically ill postoperative general surgical patients. This severity (predictive) index was based on a computerized algorithm that compares a given observed value with the frequency distributions of survivors and nonsurvivors. The difference in the mean values of this index for survivors and nonsurvivors was statistically significant (p < 0.001) during each stage of shock. Sensitivity of the index in prediction of survival ranged from 70–93% depending upon stage, the specificity of the index ranged from 76–92%, and the predictive accuracy ranged from 87–96%. The severity index is used as a process measure to track the course of critically ill patients and to evaluate the efficacy of alternative therapies.