Heart failure (HF) is a significant cause of morbidity and mortality worldwide. Acute HF is the leading medical cause of hospitalization among people aged > or = 65 years in the United States, European countries, Australia, and New Zealand. Patients hospitalized with HF are at particularly high risk for early mortality and rehospitalization. Outcomes during and after an HF hospitalization are, however, highly variable. The inhospital mortality rates reported for patients hospitalized with HF has varied greatly, ranging from 2% to 20%. Mortality rates in the first 30 days and 1 year after hospitalization, although high, also significantly vary. A large number of individual variables predictive of prognosis in patients hospitalized with acute HF exist. More recent studies have developed and validated models to allow clinicians to more reliably identify patients with HF at lower, intermediate, and higher risk for mortality based on patient characteristics, vital signs, and laboratories at the time of admission. Identification of individual prognostic variables and use of clinical risk prediction tools may be helpful in triaging patients with acute HF and guiding medical decision making. This article will discuss the epidemiology, mortality predictors, and risk stratification models for patients hospitalized with acute HF and provide a perspective on the value of integrating these tools in clinical practice.