This research aims to improve the performance of solar dryers, especially during periods of low light, through the integration of optimization techniques involving phase change materials (PCMs). Solar drying is recognized as a sustainable method for preserving agricultural products; however, its effectiveness is often constrained by variable solar radiation. The main objective of this study was to develop a mathematical model with parameters that enhance the efficiency of solar dryers using PCM to regulate the drying temperature and boost overall performance. The research utilized both experimental and computational methods, including the creation of a mathematical model and CFD simulations. The key findings indicate that incorporating PCM significantly reduces drying time by maintaining a more consistent temperature within the drying chamber, even under low sunlight conditions. The mathematical model successfully predicted the dryer’s performance, and the simulation outcomes closely aligned with the experimental results. Additionally, the analysis of the linear programming problem (LLP) highlighted the significance of optimizing solar intensity to improve energy efficiency. In summary, this study demonstrates that solar dryers enhanced with PCM provide a practical and efficient approach to improving reliability and performance, particularly in areas with inconsistent solar availability.