This study unveiled the potential of Monte Carlo Simulation for enhancing inventory management within the value-added wood products industry, a domain previously underexplored in this context. An in-depth case analysis of a furniture manufacturer delineated a methodical approach encompassing demand forecasting, seasonality adjustments, and inventory parameter optimization. The study’s findings demonstrated substantial cost reductions, highlighting a 17.31% decrease in total inventory management costs and a 20.72% improvement in holding costs. Beyond its immediate practical implications for the wood furniture sector, this research contributes to the broader academic discourse by showcasing a novel application of Monte Carlo Simulation. It paves the way for future inquiries into advanced demand forecasting and inventory optimization methodologies, promising enhanced operational efficiency and strategic planning across various manufacturing domains.