In multidimensional modeling, fuels have been represented predominantly by single components, such as octane for gasoline. Several bicomponent studies have been performed, but these are still limited in their ability to represent real fuels, which are blends of as many as 300 components. This study outlines a method by which the fuel composition is represented by a distribution function of the fuel molecular weight. This allows a much wider range of compositions to be modeled, and only requires including two additional “species” besides the fuel, namely the mean and second moment of the distribution. This approach has been previously presented but is applied here to multidimensional calculations. Results are presented for single component droplet vaporization for comparison with single component fuel predictions, as well as results for a multicomponent gasoline and a diesel droplet. The latter illustrate the important differences between the vaporization characteristics of a multicomponent droplet compared to a single component droplet. The present approach was also applied to a gasoline hollow cone spray, illustrating not only the prediction of fuel vapor locations, but also of fuel composition variations within the spray. This, combined with knowledge of the local equivalence ratio, may be important in determining spark plug locations, unburned hydrocarbon emissions, and flame and wall quenching processes in direct injection engines.