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Many challenging statistical problems arise in the research and development of fuels and lubricants. These occur as a result of both economic and environmental constraints since fuels and lubricants are very costly to engine test and must be blended in such a way as to achieve maximum energy efficiency. Engineers are continually faced with devising statistical experiments and analyzing the resultant data to determine how fuel economy or engine performance is affected by changes in fuels and lubricants. Examples of such efforts include predicting how alternative fuels improve mileage, determining the effect of fuel additives on engine performance, and determining the fuel efficiency encountered when using multi-viscosity oils. In this paper some of the statistical techniques that are useful in designing such experiments and in developing useful prediction equations are presented.