Negotiating the complexities of wildlife management increasingly requires new approaches, especially where data may be limited. A robust combination of traditional ecological knowledge (TEK) and western science has the potential to improve management decisions and enhance the validity of ecological inferences. We examined the strengths and weaknesses of predicting woodland caribou (Rangifer tarandus caribou) habitat selection with resource selection functions (RSF) based on western science and TEK-based models within the territory of the Taku River Tlingit First Nation of northern British Columbia. We developed seasonal RSF models with data from 10 global positioning system collared caribou. We generated TEK-based habitat suitability index models from interviews with Taku River Tlingit members. We tested the ability of both habitat models to spatially predict the occurrence of collared caribou locations. To portray differences between the models, we statistically and visually compared the spatial predictions of TEK and RSF modeling approaches using Kappa statistics and k-fold cross validation. Kappa statistics of habitat ranks from the models showed substantial agreement during summer (K = 0.649) and fair agreement during winter (K = 0.337). We found that both TEK and RSF models predicted independent caribou locations (Spearman's rank correlations from k-fold cross-validation ranged from 0.612 to 0.997). Differences in model performance were a result of RSF models predicting more relatively high quality habitat than TEK models. Given the widespread declines of woodland caribou across the boreal forest of Canada, and the requirement of the Canadian Species at Risk Act to incorporate both traditional and western science approaches into recovery planning, our results demonstrate that TEK-based habitat models can effectively inform recovery planning for this imperiled species. © 2013 The Wildlife Society.