Nature’s contributions to people (NCP) provided by ecosystem functions and services are essential for human well-being, and many are in danger of disruption due to environmental change. Crop pollination, pest control, waste decomposition, flood attenuation, carbon sequestration, and others are dependent upon particular species or functional groups. However, models that make predictions of NCP and map them over landscapes have traditionally relied on biophysical variables (e.g., land cover, topography) and have not typically employed biodiversity data. Considering the strong links between NCP and biodiversity demonstrated by years of research, international consortia now advocate strongly for including biodiversity models into NCP workflows, though new methods are adopted slowly. Species distribution models, which predict species’ habitat associations and range extents, and macroecological models, which predict biodiversity patterns, are two kinds of biodiversity models that have advanced rapidly in recent years and should help improve predictions of NCP that rely on species and ecological communities. These models use environmental data as predictor variables, and new remote sensing technology and datasets present a critical opportunity to make accurate predictions of range dynamics at fine scales in both space and time. I will present on several methodological advances in biodiversity modeling, how they can be paired with new remote sensing data, and how these together can be harnessed to improve NCP predictions for the present and under future global-change scenarios.