OBJECTIVES: This study aimed to identify the spatial trends of canine leptospirosis, and predict the likelihood of leptospirosis events based on environmental and socio-economic risk profiles across the United States. METHODS: We analyzed 87,355 serological (hereafter MAT) canine leptospirosis results (2000-2014) from IDEXX Laboratories Inc. with percentage of test-positive data aggregated by county. MAT titers at a dilution of ≥1:800 were considered positive. Spatial cluster analyses were calculated using ArcGIS ver.10.2, to identify canine leptospirosis clusters and hotspots. Boosted-regression trees were developed using the dismo package in the statistical software R to identify the probability of a dog testing positive for leptospirosis using 31 selected variables for climate and precipitation, dog ownership, landscape composition, and mammal and rodent diversity. Explanatory variables included climate, land cover type, and socio-economic factors. The upper Midwest and parts of the Southeast were poorly represented in testing data. We focused on climatic and environmental risk factors to understand the dynamics of canine leptospirosis and create a risk profile even in areas where data is sparse. RESULTS: Statistical analysis highlighted environment (e.g., precipitation and temperature) and land use (e.g., residential areas with houses built on large lots) as influencing the variation of canine leptospirosis risk in different counties of the US. The results of this study are accessible to both veterinarians and pet owners through a dedicated webpage https://www.zoetisus.com/conditions/dogs/leptospirosis/index.aspx