The present study uses a systematic approach to explore the phytochemical composition of medicinal plants from Uttarakhand, Western Himalaya. The phytochemical composition of medicinal plants was analyzed based on (i) the presence of different chemical groups and (ii) bioactive compounds. The Generalized Additive Model(GAM) analysis was used to predict the occurrence of chemical groups and active compounds across different eco-climatic zones and the elevation in Uttarakhand. A total of 789 medicinal plants represented by 144 taxonomic families were screened to explore the phytochemical diversity of the medicinal plants of Uttarakhand. These medicinal plant species are signified in different life forms such as herbs (58.86%), shrubs (18.24%), trees (17.48%), ferns (2.38%), and climbers (2.13%). The probability of occurrence of the chemical groups found in tropical, sub-tropical, and warm temperate eco-climatic zones, whereas active compounds have a high Probability towards alpine, sub-alpine, and cool temperate zones. The GAM predicted that the occurrence of species with active compounds was declining significantly (p < 0.01), while total active compounds increased across elevation (1000 m). While the occurrence of species with the chemical group increased, total chemical groups were indicated to decline with increasing elevation from 1000 m (p < 0.000). The current study is overwhelmed to predict the distribution of phytochemicals in different eco-climatic zones and elevations using secondary information, which offers to discover bioactive compounds of the species occurring in the different eco-climatic habitats of the region and setting the priority of conservation concerns. However, the study encourages the various commercial sectors, such as pharmaceutical, nutraceutical, chemical, food, and cosmetics, to utilize unexplored species. In addition, the study suggests that prioritizing eco-climatic zones and elevation based on phytochemical diversity should be a factor of concern in the Himalayan region, especially under the climate change scenario.