Monitoring land use/land cover (LULC) dynamics facilitates effective management and mitigation measures by providing timely and accurate information on the landscape. This study investigates LULC dynamics in Sagarmatha National Park (SNP), one of the most popular destinations for mountain tourism, and Khaptad National Park (KNP), which are emerging destinations, though popular among domestic tourists. A random forest classification algorithm was employed to generate LULC dynamics using Landsat data. High-resolution Planet Scope images and Google Earth images were used for accuracy assessment. Archived tourist and climatic data were analyzed to explore the impacts on LULC change. Cellular automata–artificial neural network (CA-ANN)-based LULC predictions were employed to predict future LULC. LULC dynamics of SNP revealed an increase in bare land, grassland, shrubland, glacial lakes, agriculture, and water bodies; however, snow/glacier and forest cover experienced substantial decreases of 140.25 km2 and 15.36 km2, respectively, from 1989 to 2021. In KNP, LULC dynamics showed an increasing trend in grassland, agriculture, water bodies, and bare land; however, forest and shrubland experienced a decrease of 18.63 km2 and 10.48 km2. The forest loss (19.33 km2) in the buffer zone of KNP was greater compared to the buffer zone of SNP (13.45 km2). The increment in built-up area was 0.80 km2 in SNP and 1.11 km2 in KNP, indicating escalating tourist activities and population growth. For SNP, the mean annual precipitation and temperature data from 1994 to 2023 showed decreasing and increasing patterns, respectively. However, the mean annual precipitation and temperature trends in KNP demonstrated an increasing pattern. Under the business-as-usual scenario, the estimated forest loss will be 1.61 km2 in SNP by 2032 and 23.8 km2 in KNP by 2030. A significant decline in snow/glaciers is projected for the core zone of SNP, with a loss of 22.84 km2 expected by 2032. This study provides a baseline information on LULC changes in SNP and KNP. Further, it showcases the necessity of diversified national park policies as per the requirement.