Climate change causes far-reaching disruption in nature, where tolerance thresholds already have been exceeded for some plants and animals. In the short term, deer may respond to climate through individual physiological and behavioral responses. Over time, individual responses can aggregate to the population level and ultimately lead to evolutionary adaptations. We systematically reviewed the literature (published 2000–2022) to summarize the effect of temperature, rainfall, snow, combined measures (e.g., the North Atlantic Oscillation), and extreme events, on deer species inhabiting boreal and temperate forests in terms of their physiology, spatial use, and population dynamics. We targeted deer species that inhabit relevant biomes in North America, Europe, and Asia: moose, roe deer, wapiti, red deer, sika deer, fallow deer, white-tailed deer, mule deer, caribou, and reindeer. Our review (218 papers) shows that many deer populations will likely benefit in part from warmer winters, but hotter and drier summers may exceed their physiological tolerances. We found support for deer expressing both morphological, physiological, and behavioral plasticity in response to climate variability. For example, some deer species can limit the effects of harsh weather conditions by modifying habitat use and daily activity patterns, while the physiological responses of female deer can lead to long-lasting effects on population dynamics. We identified 20 patterns, among which some illustrate antagonistic pathways, suggesting that detrimental effects will cancel out some of the benefits of climate change. Our findings highlight the influence of local variables (e.g., population density and predation) on how deer will respond to climatic conditions. We identified several knowledge gaps, such as studies regarding the potential impact on these animals of extreme weather events, snow type, and wetter autumns. The patterns we have identified in this literature review should help managers understand how populations of deer may be affected by regionally projected futures regarding temperature, rainfall, and snow.