Genetic variants associated with complex traits often lie in distal enhancers. While candidate enhancers have been mapped genome-wide, their functional state and gene targets in specific cell types remain unclear. Here, we present AstroREG, a resource of enhancer–gene interactions in human primary astrocytes, generated by combining CRISPR interference (CRISPRi), single-cell RNA-seq, and machine learning. By functionally testing nearly 1,000 PsychENCODE enhancers, we identified over 150 regulatory interactions, revealing enhancers that control key astrocyte functions and genes implicated in Alzheimer’s disease The CRISPRi screen also provided valuable ground-truth data from a primary cell type for training and benchmarking prediction models of enhancer activity. We thus developed EGrf, a random forest model trained on these data, and applied it genome-wide to predict regulatory interactions with high specificity Together, these data offer a comprehensive functional map of enhancer mediated regulation in a key glial cell type in brain function and disease.