Background Acute heart failure is a common reason for admission, and outcome is often poor. Improved prognostic risk stratification may assist in the design of future trials and in patient management. Using data from a large randomized trial, we explored the prognostic value of clinical variables, measured at hospital admission for acute heart failure, to determine whether a few selected variables were inferior to an extended data set. Methods and Results The prognostic model included 37 clinical characteristics collected at baseline in PROTECT, a study comparing rolofylline and placebo in 2033 patients admitted with acute heart failure. Prespecified outcomes at 30 days were death or rehospitalization for any reason; death or rehospitalization for cardiovascular or renal reasons; and, at both 30 and 180 days, all-cause mortality. No variable had a c-index >0.70, and few had values >0.60; c-indices were lower for composite outcomes than for mortality. Blood urea was generally the strongest single predictor. Eighteen variables contributed independent prognostic information, but a reduced model using only 8 items (age, previous heart failure hospitalization, peripheral edema, systolic blood pressure, serum sodium, urea, creatinine, and albumin) performed similarly. For prediction of all-cause mortality at 180 days, the model c-index using all variables was 0.72 and for the simplified model, also 0.72. Conclusions A few simple clinical variables measured on admission in patients with acute heart failure predict a variety of adverse outcomes with accuracy similar to more complex models. However, predictive models were of only moderate accuracy, especially for outcomes that included nonfatal events. Better methods of risk stratification are required. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00328692 and NCT00354458.