The intercountry conflicts affect in a variety of ways and the magnitude of effects varies according to the characteristics of the concerned area. Civilians in conflict are often deprived of their income sources and pushed to acute food insecurity, such as the case of the Nuba Mountains of Sudan. Disruption of food systems and markets resulted in higher food prices and shortages of water and fuel, or the food itself. The war also impacts the soil structure and physicochemical properties, especially in the Landmines area, where explosive remnants of war and improvised explosive devices destroy farmland, mills, storage facilities, and machinery. Besides that, increasing insecurity and roadblocks prevented humanitarian convoys from reaching the most vulnerable. Therefore, this chapter aims to explore, analyze, and predict the spatial relationships that affect the collection of Non-Timber Forest Products (NTFPs) using geostatistical analyst tools. This research uses disaggregate statistics to test and model such a relationship, making it a viable methodology for studying NTFPs, associated with household food supply in Nuba Mountains. The study utilized ESRI ArcGIS software version 10.1 for computation, exploratory analysis, mapping, and visualization. Ordinary Least Squares, Geographically Weighted Regression, and spatial autocorrelation analysis were used to map spatial patterns, test relationships, geo-visualize, and check for redundancy among the explanatory variables. These models allowed the pattern of association to be visualized on a map and all statistical values to be spatially represented on raster maps. The research concluded with some recommendations to guide regulators, policymakers, and development agencies in making interventions that will have sustainable and equitable implications.