Salvia leriifolia Benth. is an endangered medicinal plant endemic to northeastern Iran. Its fragmented distribution, coupled with overharvesting for medicinal use and grazing pressure, has intensified the need for evidence-based conservation planning. Accordingly, this study employed the Maximum Entropy (MaxEnt) model to identify environmentally suitable habitats and determine the principal environmental drivers governing the distribution of S. leriifolia in the Torbat-Heydarieh and Zaveh regions of northeastern Iran. A total of 81 spatially rarefied occurrence records and 29 environmental predictors, including 19 bioclimatic, 3 topographic, and 7 edaphic variables, were initially considered. To improve model robustness and ecological interpretability, multicollinearity among predictors was evaluated prior to model calibration. The resulting model showed excellent predictive performance (test AUC = 0.934). Jackknife analysis identified annual precipitation (Bio12), maximum temperature of the warmest month (Bio5), precipitation of the wettest quarter (Bio16), elevation (DEM), and soil electrical conductivity (EC) as the principal factors shaping habitat suitability. The model predicted 31,475 ha (5% of the study area) as suitable habitat (probability > 0.70), primarily concentrated in the southern and northern sectors of the study area. Beyond identifying priority habitats for conservation, the resulting suitability map provides a practical decision-support tool for field surveys, habitat restoration, and future reintroduction programs, thereby contributing to the evidence-based conservation and long-term management of this threatened medicinal species.