We assessed the influence of environmental variables (elevation, stream order, distance from source, catchment area, slope, stream width, and fish species richness) on the co-occurrence patterns of the minnow, the stone loach, and the gudgeon at the stream system scale. A total of 474 sites were classified according to the seven variables using the Self-Organizing Map (neural network), and three clusters were detected (k-means algorithm). The frequency of the various fish co-occurrence patterns was calculated for each cluster, and general linear modeling was used to specify the conditions that predict the occurrence of each species. Piedmont streams were more likely to support coexisting gudgeon and minnow populations because of higher probabilities of occurrence for both species. The higher co-occurrence frequency for the three species together in headwater streams resulted from lower occurrence frequencies in gudgeon and minnow. Focusing on areas that favor the co-occurrence of species may enhance the effectiveness of conservation projects.