<p>In the context of global change, ensuring national food security and achieving sustainable development of agricultural production systems have become major challenges worldwide. To address these issues, regional-scale crop growth and associated process (CROP-AP) models, with their robust simulation and predictive capabilities, have emerged as important tools for studying a wide range of issues relating to agricultural production at river basin, national, and even global scales. Here, we provide a systematic review of the advances of regional-scale CROP-AP models. First, regional-scale CROP-AP models are categorized based on model characteristics: statistical models, crop growth models, hydrology-crop coupling models, and ecosystem models. The origin, development, principle, structure, and application of each model type are introduced. Then, the main functions of regional-scale CROP-AP models are critically reviewed from five aspects: crop yield prediction, crop water consumption, agricultural non-point source pollution, greenhouse gas emissions, and climate change impact and responses. Finally, the future development trends and research priorities of regional-scale CROP-AP models are explored from six key perspectives: model validation and calibration, the ability to simulate the coupling of crop physiology and human activities, enhancing model scalability, multi-model ensembles, data and code sharing, and the integration of artificial intelligence. This review aims to provide comprehensive references and insights for the further development and application of large-scale, high-precision CROP-AP models.</p>