Global climate change has increased the instances and severity of wildfires on a global scale. While wildfires are a form of natural disturbance, the predicted rise in fire occurrences represents a growing concern for wildlife management and susceptible human populations. Evaluating the danger of fire occurrences and potential consequences for both human and wildlife populations is referred to as wildfire risk. The concept of wildfire risk is comprised of both susceptibility (probability of fire) and vulnerability (impact on ecology and society). In this study we aim to develop a model for wildfire risk that can be applied to topographically complex regions which encompass both aspects of high susceptibility and vulnerability. The model was applied to the Southern Interior ecoregion in British Columbia which contains regions of urban development, valuable ecology, as well as a substantial amount of fire occurrences. Our results showed unexpected degrees of risk, predominately around regions where heavily weighted sets of data are sparse and rely on interpolation methods for processing. We propose, acquiring more data is in order to achieve greater results for a comprehensive wildfire risk model. Yet our work lays the foundation for future models, and reveals the essential data needs required for future research.