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The rapid increase in the use and development of statistical design of experiments (DoE), particularly in pharmaceutical process development, has become increasingly important over the last decades. This rise aligns with Green Chemistry Principles, seeking reduced resource usage and heightened efficiency. In this study, we employed a comprehensive design of experiments (DoE) approach to optimize the catalytic conversion of 1-decene to n-decanal through direct Wacker-type oxidation using the previously determined efficient PdCl2(MeCN)2 catalytic system. The aim was to maximize selectivity and conversion efficiency. Through systematic variation of seven factors, including substrate amount, catalyst and co-catalyst amount, reaction temperature, reaction time, homogenization temperature, and water content, this study identified critical parameters influencing the process to direct the reaction toward the desired product. The statistical analysis revealed high significance for both selectivity and conversion, with surface diagrams illustrating optimal conditions. Notably, catalyst amount emerged as a pivotal factor influencing conversion, with reaction temperature and co-catalyst amount significantly affecting both conversion efficiency and selectivity. The refined model demonstrated strong correlations between predicted and observed values, highlighting the impact of these factors on both selectivity and conversion.