Sustainable production of alcohols from renewable sources represents a very important environmental and industrial technology. In this work, response surface methodology (RSM) was employed to study the influence of various process parameters, such as temperature, pressure and substrate to catalyst ratio on the selective hydrogenation of dimethylfuran (DMF) as a model compound for bio-derived furans. The aim was to maximize the yield of the alcoholic product (2-hexanol) using a bifunctional catalyst system composed of platinum supported on a Keggin-polyoxometalate under mild hydrogenation conditions. Hereby, the RSM was used in order to build four predictive models capable of estimating the yield of each product resulting from the hydrogenation reaction. The performance of the prediction models was examined both statistically and experimentally confirming that the predictions are in an excellent agreement with the experimental data. Numerical optimization was performed to reveal the optimal operating conditions to achieve maximum yield of the alcoholic product. With the help of Design of Experiments (DoE) and desirability function approach for optimization, we were able to achieve 78% 2-hexanol yield at complete DMF conversion using a Pt/K3PW12O40 catalyst under mild hydrogenation conditions of 80°C and 5-15 bar hydrogen pressure.