The accurate and uniform distribution of granular fertilizers is critical to optimizing crop yield, minimizing nutrient loss, and promoting sustainable agricultural practices. In precision agriculture, variable-rate fertilization (VRF) systems have emerged as an essential technology that adjusts fertilizer input according to real-time spatial and temporal field variability. Among various VRF mechanisms, centrifugal spreaders have gained widespread adoption due to their operational simplicity, high efficiency, and compatibility with a wide range of granular materials. However, achieving consistent spreading performance under varying working conditions remains a technical challenge, particularly due to the complex dynamics involved in particle flow, machine structure, and operational parameters. Discrete Element Method (DEM)-based simulation has become an increasingly powerful tool for analyzing and optimizing the performance of fertilizer applicators. DEM offers a high-fidelity, particle-level understanding of interactions within the spreading system, thereby enabling engineers to predict material trajectories, identify uneven distribution patterns, and propose design improvements. The studies presented in this chapter focus on the numerical modeling and optimization of centrifugal variable-rate fertilizer applicators using DEM and CFD-DEM coupling methods. These investigations focus on critical engineering challenges, including the effects of disc geometry, particle characteristics, and rotational speed on distribution uniformity, with the goal of developing effective strategies for structural and operational optimization. These studies collectively address crucial engineering problems, such as the influence of disc geometry, particle properties, and rotational speed on distribution uniformity, and present effective strategies for structural and operational optimization. By integrating simulation and experimental approaches, they contribute to the theoretical basis and practical advancement of VRF technologies. This chapter aims to consolidate and critically examine their methodologies, findings, and implications, laying the groundwork for the intelligent design and optimization of next-generation fertilizer application systems.