We investigated survival and cause-specific mortality of mule deer (Odocoileus hemionus) on 3 distinct winter ranges in southwest Idaho from 1992 to 1997 to identify demographic variation and potential limiting factors based on a sample of 447 radiocollared deer. During winters 1995–1996 and 1996–1997, we modeled overwinter fawn mortality based on early winter mass, sex, activity, and habitat use variables. Annual survival rates of adult mule deer varied among the 3 adjacent study areas (χ²₂ = 10.93, P = 0.004). Overwinter deer survival also varied among study areas (χ²₂ = 8.00, P = 0.018), and the study area × year, study area × sex, and study area × age interactions were all significant (P ≤ 0.018). Overwinter survival differences among the study areas were not consistent over time or among sexes and ages of deer. Winter malnutrition was the main cause of mortality for both adults and fawns during the severe winter of 1992–1993, when overall survival was low. Excluding harvest, predation was the major proximate cause of deer mortality during 1993–97 when overall survival was higher. The probability of winter fawn mortality increased with lower mass (χ²₁ = 7.38, P = 0.007), being male (χ²₁ = 5.61, P = 0.018), smaller group sizes (χ²₁ = 3.62, P = 0.057), and using steeper slopes (χ²₁ = 3.05, P = 0.081). Smaller group sizes and use of steep slopes corresponded to conditions where predators were more successful. Our findings suggest that coyote (Canis latrans) predation was largely compensatory whereas mountain lion (Puma concolor) predation was apparently independent of animal condition and dependent more on deer habitat use. Early winter fawn mass was a better predictor of overwinter fawn survival than a suite of winter resource use variables, lending further support for use of fawn mass to predict winters where fawn mortality may be high. No single population in this study could be used to make reliable inferences regarding deer survival in the other populations. Survival rate measurements should be used cautiously to make inferences in populations where survival has not been directly measured.