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Land-use transition is one of the most profound human-induced alterations of the Earth’s system. It can support better land management and decision-making for increasing the yield of food production to fulfill the food needs in a specific area. However, modeling land-use change involves the complexity of human drivers and natural or environmental constraints. This study develops an agent-based model (ABM) for land use transitions using critical indicators that contribute to food deserts. The model’s performance was evaluated using Guilford County, North Carolina, as a case study. The modeling inputs include land covers, climate variability (rainfall and temperature), soil quality, land-use-related policies, and population growth. Studying the interrelationships between these factors can improve the development of effective land-use policies and help responsible agencies and policymakers plan accordingly to improve food security. The agent-based model illustrates how and when individuals or communities could make specific land-cover transitions to fulfill the community’s food needs. The results indicate that the agent-based model could effectively monitor land use and environmental changes to visualize potential risks over time and help the affected communities plan accordingly.