Impact assessments increasingly rely on models to project the potential impacts of climate change on species distributions. Ecological niche models have become established as an efficient and widely used method for interpolating (and sometimes extrapolating) species’ distributions. They use statistical and machine-learning approaches to relate species’ observations to environmental predictor variables and identify the main environmental determinants of species’ ranges. Based on this estimated species–environment relationship, the species’ potential distribution can be mapped in space (and time). In this chapter, we explain the concept and underlying assumptions of ecological niche models, describe the basic modelling steps using the silvereye (Zosterops lateralis) as a simple real-world example, identify potential sources of uncertainty in underlying data and in the model, and discuss potential limitations as well as latest developments and future perspectives of ecological niche models in a global change context.