Circuit theory provides a more accurate method for predicting gene flow in plant and animal populations compared to traditional models. This study applies circuit theory to improve gene flow predictions by considering all possible pathways connecting populations, which conventional models fail to do. The isolation-by-resistance (IBR) model, based on circuit theory, outperformed conventional gene flow models in predicting genetic differentiation among populations of threatened species, such as the big-leaf mahogany and the wolverine. The IBR model accounts for multiple pathways and habitat configurations, leading to more accurate predictions of gene flow and genetic structure. It also provides a stronger theoretical foundation than conventional isolation-by-distance (IBD) models or least-cost path (LCP) models. The study used genetic and landscape data to test the IBR model, finding that it consistently outperformed other models in predicting genetic differentiation. The results suggest that barriers are less important in structuring populations than previously thought, and that range shape significantly affects genetic structure. The IBR model is more robust to alternative model parameterizations and provides better predictions of gene flow in complex landscapes. The study highlights the importance of incorporating spatial heterogeneity in landscape genetics and conservation planning. Circuit theory offers a promising approach for understanding and predicting gene flow in fragmented landscapes, with potential applications in ecology, evolution, and conservation.Circuit theory provides a more accurate method for predicting gene flow in plant and animal populations compared to traditional models. This study applies circuit theory to improve gene flow predictions by considering all possible pathways connecting populations, which conventional models fail to do. The isolation-by-resistance (IBR) model, based on circuit theory, outperformed conventional gene flow models in predicting genetic differentiation among populations of threatened species, such as the big-leaf mahogany and the wolverine. The IBR model accounts for multiple pathways and habitat configurations, leading to more accurate predictions of gene flow and genetic structure. It also provides a stronger theoretical foundation than conventional isolation-by-distance (IBD) models or least-cost path (LCP) models. The study used genetic and landscape data to test the IBR model, finding that it consistently outperformed other models in predicting genetic differentiation. The results suggest that barriers are less important in structuring populations than previously thought, and that range shape significantly affects genetic structure. The IBR model is more robust to alternative model parameterizations and provides better predictions of gene flow in complex landscapes. The study highlights the importance of incorporating spatial heterogeneity in landscape genetics and conservation planning. Circuit theory offers a promising approach for understanding and predicting gene flow in fragmented landscapes, with potential applications in ecology, evolution, and conservation.