Predation can shape community structure, so understanding the diet of predators is an important aspect of ecology. Stable isotope analysis using Bayesian mixing models is a potentially powerful method of estimating diet, but results are often ambiguous. A commonly cited advantage of Bayesian mixing models is the ability to include informative priors, which can improve precision and accuracy of mixing model results. However, factors such as a large number of potential prey and high amounts of variation and correlation among isotopic signatures of prey can lead to imprecise estimate of diet when Bayesian mixing models are used. In this study, we tested the efficacy of using Bayesian mixing models for stable isotopes to estimate the diet of Arctic Peregrine Falcon (Falco peregrinus tundrius) nestlings in Nunavut, Canada, consuming a diversity of terrestrial and marine prey. In addition to stable isotopes, we also estimated diet composition by monitoring peregrine nests with motion-sensitive cameras. Stable isotope analysis was conducted using blood plasma samples collected weekly from nestlings and tissue samples from all prey groups they consumed. Uninformed mixing models, based on stable isotopes alone, had wide credible intervals around diet estimates, which indicated lemmings (Lemmus trimucronatus and Dicrostonyx groenlandicus) were the main contributor to diets. In contrast, diet estimated with motion-sensitive cameras had high precision and indicated that insectivorous birds were the dominant prey consumed. When informative priors from motion-sensitive camera data were included in Bayesian mixing models, resulting diet estimates had narrow credible intervals and generally reflected the priors. We conclude that with our data stable isotope analysis alone is inaccurate for monitoring the diet of Arctic Peregrine Falcons, but motion-sensitive cameras at nest sites provide a viable alternative method.