Abstract. Subedi PB, Mahara S, Paudel S , Bhandari J, Thagunna RS. 2023. Agroforestry potential of Kanchanpur District, Nepal using remote sensing and Geographic Information System. Asian J Agric 7: 65-74. Researchers are interested in agroforestry because it can reduce poverty and land degradation, mitigate climate change, and improve food security. This study aimed to determine the land potential for agroforestry in Kanchanpur District, Nepal, using Geographic Information System modeling concepts and a variety of ancillary (soil fertility) and satellite data (Digital Elevation Model, wetness, Normalized Difference Vegetation Index, and Land Use Land Cover) sets. It was accomplished by logically integrating various thematic layers in the GIS domain. For Kanchanpur District of Nepal's Sudurpaschim Province, agroforestry suitability maps showed that 76.14 percent was very high suitable, 3.12 percent was highly suitable, 13.89 percent was medium, 5.67 percent was low suitable, and 1.15 percent was very low suitable. The use of remote sensing and GIS to find suitable land for agroforestry have significant impacts, which will significantly aid in the study of agroforestry practices and the estimation of crucial factors for optimal productivity. Such analyses and results will undoubtedly assist agroforestry policymakers, and planners put it into practice and expanding in new areas. GIS modeling has enormous potential for land resource mapping, eventually contributing to the benefit of poor rural people, especially farmers, and helping ensure food and environmental security and a sustainable livelihood.