This paper presents a systematic computer aided technique to design a sustainable (safe, environmentally friendly and economical) tailor-made "green diesel" blend that satisfies a set of desirable target properties. In this work, the software, Integrated Computer Aided System (ICAS) was used to predict the green diesel properties. The blending model is formulated to identify a set of feasible mixture blends that satisfy the desirable target properties such as density and viscosity. The blend design problem is formulated as an NLP problem and solved through GAMS. Application of the systematic technique yields several promising green diesel blends. Four final candidate blends were selected based on three key criterion, i.e. cost, sulfur content and carbon dioxide emissions. The results show that the best diesel contains 82.4% diesel, 16.6% butanol and 1% butyl levulinate. This diesel blend contributes to the reduction of CO2 emission and sulfur content by up to 15% and 17%, respectively. (c) 2012 Elsevier Ltd. All rights reserved.