<![CDATA[Essential oils (EOs) are valuable natural products with diverse industrial applications. The present study aimed to optimize the hydrodistillation (HD) process to maximize essential oil (EO) recovery of Eucalyptus pellita leaves. Response Surface Methodology (RSM) with a Box-Behnken Design (BBD) was employed to model and analyze the effects of three key factors: extraction time (A), agitation speed (B), and solvent-to-leaf mass ratio (C). Seventeen experimental runs were conducted by using a Clevenger apparatus. The results showed that the ANOVA quadratic models were statistically significant for both mass and yield EO, with excellent coefficients of determination (R² > 0.99), adjusted R², predicted R², adequate precision, and non-significant lack-of-fit. All three linear parameters (A, B, C) and their interactions (AB, AC, BC) had a significant impact on extraction efficiency. Nonetheless, the quadratic terms (A2, B2, C2) had a non-significant effect on the responses. The RSM predicted optimum conditions at 4.96 h, 874 rpm, and a solid-to-solvent mass ratio of 1:5.4 (g/g). This condition predicted 0.62-0.66 g of mass and 0.42-0.44% of yield EO. Experimental validation under these conditions produced an average EO mass of 0.635 g and an average yield of 0.4235%, both values closely matching the predicted outcomes. These results demonstrate the accuracy application of the RSM-BBD in optimizing HD for Eucalyptus pellita EO. The optimized parameters and validated model provide a practical and scalable framework for industrial EO production, supporting the transition from laboratory research to commercial implementation.]]>
