The goal of the present work is to establish a framework for firebrand morphology characterization. Central to this framework is the development of a simple firebrand shape classification model using multi-dimensional particle shape descriptors. This classification model is built upon a series of synthetically generated 3D particles whose shapes and sizes are chosen to be representative of actual firebrands typically encountered during vegetative and structural fuel burns. Principal Component Analysis (PCA) is applied to the synthetic dataset and used to structure the classification model. The model is then verified using 3D digital representations of real-world particles (firebrands collected during tree burns and unburned bark pieces from oak trees). The classification model, which will allow meaningful comparisons of firebrand morphological features by shape class, is expected to be gradually refined as more datasets are made available throughout the Wildland–Urban Interface (WUI) fire research community.