In this study, the discrete element method was used to optimize the bucket size for the metering device in a garlic planter for enhancing the productivity of garlic farming according to the garlic size. Statistical information concerning the actual shape of garlic cloves was incorporated, and the mechanical properties of garlic were determined using the bulk density, sliding test, and repose angle test for enhancing the fidelity of the simulation model. The optimal bucket size achieving the target plant rate of 97.5% was determined using the developed discrete element model for the three garlic size groups. The linear search method was used for optimization, and batch simulation was performed to validate the optimized results and confirm the performance index of the metering device. A Gaussian distribution based on statistical information accounted for the various garlic sizes in each group. Finally, a metering test verified the reliability of the optimization technique. The differences between the simulation and test results were within 10% for all performance indices, including missing plant rate, multi-plant rate, and planting rate, indicating the high reliability of the analysis model. Subsequently, the larger garlic groups (Groups 2 and 3) exhibited metering performance close to the target plant rate.