The demand for the energy has increased drastically as a result of the rapid growth in industrialization, urbanisation and higher standard of living. One such potential substitute to fossil fuels is biodiesel that ensures sustainable energy source. The selection of appropriate source of biodiesel and proper blending of biodiesel plays a major role in alternate energy production. In the present work, a novel hybrid Multi Criteria Decision Making (MCDM) technique was proposed to evaluate and select the optimum fuel biodiesel blend for the IC engine with conflicting criteria to enhance the energy efficiency. Exploratory analysis were carried out on a single cylinder four stroke, air cooled, constant speed, direct injection diesel engine with a rated output of 4.4 kW at 1500 rpm at different loads. Two hybrid MCDM models, namely Fuzzy TOPSIS and Fuzzy VIKOR were proposed. Fuzzy was applied to determine the relative weights of the evaluation criteria whereas TOPSIS and VIKOR were applied to obtain the final ranking of alternatives. Diesel, B20, B40, B60, B80 and B100 fuel blend alternatives are prepared by varying the proportion of biodiesel for MCDM model. Similarly BTE, MRPR, NOx CO2, CO, HC, SMOKE, ID, CD and Exhaust gas temperature were considered as the evaluation criteria. The ranking order by Fuzzy TOPSIS is based on closeness coefficient and Fuzzy VIKOR is based on VIKOR index. In Fuzzy TOPSIS, B40 stands first at 50% and 75% load conditions and second at 25% and full load conditions respectively. In Fuzzy VIKOR, B40 stands first at 25% and 50% conditions and second at no load, 75% and full load conditions respectively. The ranking of alternatives as obtained by both Fuzzy-TOPSIS and Fuzzy-VIKOR is B40 > B20 > Diesel > B80 > B60 > B100 and B40 > B20 > Diesel > B60 > B80 > B100. From the results, it was observed that both the methods indicated that B40 is the best blend to operate the engine. Hence, it is concluded that mixing 40% biodiesel with diesel is suggested as a good partial replacement for diesel. This paper highlights a new insight into MCDM techniques to evaluate the best fuel blend for the decision makers such as engine manufactures and R& D engineers to meet the fuel economy and emission norms to empower the green revolution and energy management. © 2017 Elsevier Ltd