A better understanding of the relative importance of different spatial scale determinants on fish communities will eventually increase the accuracy and precision of their bioassessments. Many studies have described the influence of environmental variables on fish communities on multiple spatial scales. However, there is very limited information available on this topic for the East Asian monsoon region, including Korea. In this study, we evaluated the relationship between fish communities and environmental variables at multiple spatial scales using self-organizing map (SOM), random forest, and theoretical path models. The SOM explored differences among fish communities, reflecting environmental gradients, such as a longitudinal gradient from upstream to downstream, and differences in land cover types and water quality. The random forest model for predicting fish community patterns that used all 14 environmental variables was more powerful than a model using any single variable or other combination of environmental variables, and the random forest model was effective at predicting the occurrence of species and evaluating the contribution of environmental variables to that prediction. The theoretical path model described the responses of different species to their environment at multiple spatial scales, showing the importance of altitude, forest, and water quality factors to fish assemblages.