Model intercomparisons are emerging as a powerful approach to improve our understanding of biodiversity and ecosystem responses to global changes, thereby supporting policy design and decision-making. However, efforts to date have focused on climate change impacts on species richness at a global scale, while regional impacts remain comparatively understudied. To address this gap, we propose a protocol for a biodiversity model intercomparison project focused on regional-to-continental scale patterns of species abundance and occurrence across space and time. This protocol covers a continuum of modeling approaches, ranging from correlative to process-explicit models. We detail the standardized input data used for model calibration –climate, land-use, and biodiversity data– and outline a common framework for model validation and performance assessment. Our protocol is structured in two phases. The first phase involves model specification, calibration, and validation using historical data, together with counterfactual experiments designed to attribute observed changes in population abundance and occurrence to different environmental drivers. In the second phase, model projections are compared under future climate and land-use scenarios. This two-phase approach enables direct comparison of model predictive performance on common benchmark data, providing an empirical basis for assessing confidence in future projections. By combining regional-scale biodiversity time series, common calibration and out-of-sample validation, and explicit representation of ecological processes, this protocol advances regional biodiversity model intercomparisons and sets the stage to reveal fundamental insights into which models, processes, and drivers determine historical and future biodiversity dynamics.