Invasive species are widely recognized as a major threat to global diversity and an important factor associated with global change. Species distribution models (SDMs) have been widely applied to determine the range that invasive species could potentially occupy, but most examples focus on predictive variables at a single spatial scale. In this study, we simultaneously considered a broad range of variables related to climate, topography, land cover, land use, and propagule pressure to predict what areas in the southeastern United States are more susceptible to invasion by 45 invasive terrestrial plant species. Using expert-verified occurrence points from EDDMapS, we modeled invasion susceptibility at 30-m resolution for each species using a maximum entropy (MaxEnt) modeling approach. We then analyzed how environmental predictors affected susceptibility to invasion at different spatial scales. Climatic and land-use variables, especially minimum temperature of coldest month and distance to developed areas, were good predictors of landscape susceptibility to invasion. For most of the species tested, human-disturbed systems such as developed areas and barren lands were more prone to be invaded than areas that experienced minimal human interference. As expected, we found that landscape heterogeneity and the presence of corridors for propagule dispersal significantly increased landscape susceptibility to invasion for most species. However, we also found a number of species for which the susceptibility to invasion increased in landscapes with large core areas and/or less-aggregated patches. These exceptions suggest that even though we found the expected general patterns for susceptibility to invasion among most species, the influence of landscape composition and configuration on invasion risk is species specific.