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Climate change is impacting species globally. Predicting which species will be impacted, where, when, and by how much, is vital to conserve biodiversity in a warming world. In this thesis, I evaluate the likely impacts of climate change on an endangered species, the African wild dog, Lycaon pictus, for which direct impacts of high ambient temperature on behaviour and recruitment have previously been identified. Wild dogs hunt mainly in daylight, and I show they are unlikely to be able to adapt to a warming climate by hunting at night. I found nocturnal hunting was constrained by the availability of moonlight, and by the need to guard pups in the den, restricting the use of cooler night-time hours. I also show high ambient temperatures are associated with increased adult mortality, appearing to increase mortality due to human causes and disease, which is linked to human pressures through transmission from domestic dogs. Having quantified the impacts of ambient temperature on key vital rates, I develop an Individual-Based Model to project the likely effects of climate change on population growth. I show that population projections for this species are sensitive to the emissions scenario and population size, with population collapse predicted for smaller populations under the worst-case scenario. Finally, I use my Individual-Based Model to make spatially explicit predictions of population changes throughout the species' remaining range. My model predicts that populations in cooler coastal regions will suffer the smallest population declines, along with populations located in East Africa. Predicted threat status of the species was dependant on the emissions scenario. My study shows how behavioural and demographic data can be used to inform conservation planning in a changing climate. My findings also inform efforts to incorporate climate change impacts into assessments of species' threat status by the IUCN Red List.