Seed coating is used to improve seed handling or target the delivery of different active ingredients: (micro)nutrients and biofortifying minerals, plant biostimulants, and plant protection compounds. One type of coating is based on using film-forming biopolymers. The coating could be applied using various equipment, including the Wurster fluidized-bed coater. Deterministic models have been proposed to predict the coating process performance in the Wurster fluidized-bed coater. However, such deterministic models do not closely match real behavior. This paper proposes a statistical model approach to optimize the mung bean seed coating with a mixture of alginate/glycerol in a Wurster fluidized bed coating process. The process was optimized for a specific case through a factorial experimental design for the following parameters: the liquid flow rate, the mass of seeds, the backpressure period, and the nozzle pressure. The statistical analysis was done using Design-Expert 11®. The formed film was analyzed by scanning electron microscopy. Finally, the germination percentage (GP), germination energy (GE), germination rate (GR), mean germination time (MGT), and vigor index (VI) were determined for the coated mung bean seeds. An algorithm is proposed to identify the optimal coating conditions in a bottom-spray Wurster fluidized-bed coater for any coating solution or seed pair.