To prospectively validate a previously developed two-factor logistic regression model as a predictor of mortality, we studied its effectiveness in predicting outcome for patients in medical intensive care units (ICUs) who had surgical laparotomy. A high-risk classification was assigned to patients with an Organ System Failure Index (OSFI) ≤3 or an APACHE (Acute Physiology and Chronic Health Evaluation) II score >18 within 24 hours of surgery. The in-hospital mortality rate of surgical patients classified as high risk (n = 32) was significantly greater than that of surgical patients classified as low risk (n = 42) (62.5% versus 9.5%; relative risk, 6.6; 95% confidence interval, 2.5 to 17.3). Mortality after surgery correlated with presence or absence of the two variables from the logistic regression model: neither present, 9.5%; APACHE II >18 present, 68.0%; OSFI ≤3 present, 75.0%; both present, 88.2%. We showed that a two-factor risk classification at the time of surgical evaluation can be used to stratify medical ICU patients according to risk of in-hospital mortality.