This study investigates the spatial and environmental patterns of cutaneous and visceral leishmaniasis across the Mediterranean region, integrating ecological, climatic, and land use variables at a regional scale. Utilizing kernel density estimation, land cover classification, Koppen climate mapping, soil type analysis, ensemble machine learning, and ecological niche clustering, the research identifies disease hotspots and key environmental predictors. Cutaneous leishmaniasis hotspots were found in southwestern Morocco, central Tunisia, the Levant, southern Turkey, and Crete, while visceral leishmaniasis clustered in central Tunisia, northern Israel, southern France, and Albania. Both diseases followed a U-shaped urbanization pattern, with cases concentrated in sparsely populated rural zones and dense urban areas. Most occurrences were associated with hot-summer Mediterranean and semi-arid climates and soil types. Random Forest and XGBoost models highlighted precipitation-related variables and specific soils as the most influential predictors. Ecological niche analysis revealed overlapping environmental spaces for both disease types, while K-means clustering defined four major environmental clusters for each. These findings offer a foundation for targeted interventions, including land rehabilitation, climateadaptive surveillance, seasonal health alerts, and integration of vector control into urban planning. Overall, the study provides a comprehensive framework for leishmaniasis monitoring and control aligned with regional environmental contexts.