The discrete element method (DEM) [1,2] has become an important numerical tool to investigate the interaction between agricultural machinery and granular agricultural materials [3-5], among other applications [6]. By allowing analysis of particle-scale dynamics and macroscopic system behavior, DEM provides valuable support for the design, optimization, and evaluation of agricultural equipment performance. This paper presents a comprehensive review of advances in the application of DEM in agricultural machinery, with a particular emphasis on material modeling, parameter calibration strategies, and simulation of machine operation processes [7,8]. First, the establishment of DEM models for major agricultural materials, including soil, seeds, and plant residues, is analyzed, highlighting commonly adopted contact models and calibration methodologies. Second, the application of DEM in the simulation of key agricultural operations, such as soil tillage, material conveying, and harvesting processes, is examined to identify current capabilities and limitations [9,10]. Finally, the main technical challenges and future research directions are discussed, focusing on improving model accuracy, validation practices, and integration with experimental and industrial workflows. DEM achieves 8–20% prediction accuracy for comparative design evaluation, persistent challenges in calibration transferability and computational cost constrain industrial-scale adoption. This paper aims to provide a structured framework to guide future developments and to promote the effective use of DEM in the design and optimization of agricultural machinery.