Forest litter is a fuel component that is important for the propagation of fire. Data describing fuel load, structure and fuel condition were gathered for two sites of Sydney Coastal Dry Sclerophyll Forest, a common vegetation type in the Sydney Basin, Australia. Surface litter from the sites was sorted into its constituent components and used to establish which component or mixture of components were the most flammable using several metrics. A general blending model was used to estimate the effect the different mixtures had on the response of the flammability metrics and identify non-additive effects. Optimisation methods were applied to the models to determine the mixture compositions that were the most or least flammable. Differences in the flammability of the two sites were significant and were driven by Allocasuarina littoralis. The presence of A. littoralis in litter mixtures caused non-additive effects, increasing the rate of flame spread and flame height non-linearly. We discuss how land managers could use these models as a tool to assist in prioritising areas for hazard reduction burns and how the methodology can be extended to other fuel conditions or forest types.