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Aquaculture is increasingly important for meeting the rising global demand for seafood. To improve the sustainability of the aquaculture industry, there have been increasing efforts to develop smart aquaculture technologies, including simulation methods, to optimize growth and feeding strategies. This study developed a simulation model, which incorporates a fish behavior model based on the Boids model and a dynamic energy budget, for the purpose of improving the efficiency of rainbow trout ( Oncorhynchus mykiss ) aquaculture. The proposed simulation method predicts the growth trajectories of individual fish and evaluates the effects of different feeding levels on fish growth and feed efficiency. The simulation results were compared with those of a live rearing experiment to evaluate its accuracy. Rainbow trout growth trajectories were accurately predicted. However, longer-term simulations showed increasing divergence between the simulated and experimental data. The proposed simulation method allows the optimization of growth and feeding efficiency under various feeding strategies. Further refinements of the simulation model, including considering density effects and parameter adjustments, may lead to more accurate long-term predictions. The simulation-based approach developed in this study will contribute to a better understanding of rainbow trout growth, with potential applications for other aquaculture species and contexts.