Hydroxylated aromatic compounds (HACs) are considered to be primary pollutants in a wide variety of industrial wastewaters. Horseradish peroxidase (HRP) is suitable for the removal of these toxic substances. However, development of a mathematical model and optimization of the HRP-based treatment considering the economical issues by novel methods is a necessity. In the present study, optimization of phenol removal from wastewater by horseradish peroxidase (HRP) was carried out using response surface methodology (RSM) and central composite design (CCD). As the initial experimental design, 2(4-1) half-fraction factorial design (H-FFD) is accomplished in triplicate at two levels to select the most significant factors and interactions in the phenol removal procedure. Temperature (degrees C), pH, concentration of enzyme (unit mL(-1)), and H202 (mM) were determined as the most effective independent variables. Finally, a fourfactor-five coded level CCD, 30 runs, was performed in order to fit a second-order polynomial function to the results and calculate the economically optimum conditions of the reaction. The goodness of the model was checked by different criteria including the coefficient of determination (R2 = 0.93), the corresponding analysis of variance ((Pmodel > F) < 0.0001) and parity plot (r = 0.96). These analyses indicated that the fitted model is appropriate for this enzymatic system. With the assumption that the minimum enzyme concentration was 0.26 unit mL(-1), the analysis of the response surface contour and surface plots defined the optimum conditions as follows: pH = 7.12, hydrogen peroxide concentration 1.72 mM, and 10 degrees C. This work improves phenol removal operation economically by applying minimum enzyme concentration and highest removal in comparison with previous studies.