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Myrica esculenta is a socio-economically important but underutilized keystone species of lesser Himalayas. The population of M. esculenta is declining in lesser Himalayas due to change in male-female ratio, habitat fragmentation, invasion by chir pine, over-exploitation, and an ever-increasing human population - with an increasing demand of land for agriculture, industries, and urbanization. The shrinking habitat along with unknown genetic diversity may hinder the application of conservation and genetic improvement of this species. The present research work was carried out to map the geographical distribution and predict the potential occurrence of M. esculenta in Uttarakhand, India. The Remote Sensing and Geographical Information System (RS & GIS) based technology is utilized for prediction modeling and eco-distribution mapping. In total, 1022 species occurrence geospatial data were recorded for M. esculenta. The field surveys provided wide-range of slope, aspect and elevation of the species. The well distributed geo-coordinates (30.52%) were used in the Maxent model for predicting the distribution. Digital Image Processing (DIP) was done through geo-model tools. The results of Maxent model was found to be highly accurate with a statistically highly significant AUC value of 0.913 +/- 0.020. The Jackknife test revealed temperature seasonality (Bio 4), mean temperature of the wettest quarter (Bio 8), slope and precipitation of driest month (Bio 14) contributed significantly in predicting the distribution. The eco-distribution map, prepared using the LANDSAT-8 satellite imagery, showed 477.26 km(2) geographical area under M. esculenta distribution. Within the total area, 111.17, 260.52 and 105.57 km(2) were observed under very dense, moderately dense and open forest, respectively. The potential distribution area calculated in ASTER - GDEM satellite image was 2017.14 km(2). The satellite-based distribution map would be useful for forest departments, scientists, and researchers to locate actual M. esculenta distribution sites for future in situ and ex situ conservation. This approach could be promising in overlaying genetic diversity values over the map and could be effectively utilized in M. esculenta conservation, restoration and management programmes. The present study provides the first eco-distribution map and generated base-line data of M. esculenta in Uttarakhand, India.