This study examined the impact of climatic variability on food security in rural communities across three key districts in South Punjab, Pakistan. A mixed-methods approach was employed, combining Geographic Information System (GIS) techniques to map food security zones and socioeconomic data to compute a food security index. Primary data were collected from 399 respondents through a field survey using a disproportionate stratified random sampling technique in selected union councils of Bahawalpur, Rahim Yar Khan, and Rajanpur districts. Climate data from 1991 to 2021 were analyzed using multiple linear regression analysis. Advanced statistical methods, including categorical principal component analysis, global Moran's I, and Anselin local Moran's I, were utilized to identify spatial clusters of food security. The analysis revealed regional disparities: Bahawalpur demonstrated high food security, Rajanpur exhibited severe food insecurity, and Rahim Yar Khan showed mixed results. The study found that expanding agricultural crop areas improved food availability, although climatic factors had a complex impact on the yields. Higher temperatures decreased wheat production in Rajanpur but enhanced yields in Bahawalpur and Rahim Yar Khan. Non-linear Principal Component Analysis identified key factors, such as livelihoods, asset accessibility, and desertification, which explained 46% of the variation in food security. These results underscore the need for adaptive strategies, including the use of advanced technologies and improved irrigation, to mitigate the effects of climate change and support agriculture in South Punjab.