As wildfires continue to grow more frequent and severe in California, it is increasingly important to understand how deer herds respond to these large disturbances. Diet is an important component of herbivore life history that can be impacted by wildfire, potentially affecting behavior and survival of deer. This project aims to asses changes to deer diet before and after the Ranch Fire of 2018 in the Mendocino National Forest of Northern California using metabarcoding of fecal pellet samples. Dietary metabarcoding is a relatively new method that detects dietary items using trace amounts of DNA in fecal pellets or other forms of ingesta. The process involves extraction of DNA from fecal pellets, followed by amplification via polymerase chain reaction of a targeted DNA marker, such as the trnL regions of the chloroplast genome. The products are then sequenced on a high-throughput platform and sequences sorted bioinformatically to identify multiple taxa at once and determine the dietary content of a sample. Here we describe our study design, including sample collection sites before and after the fire, our metabarcoding process, preliminary findings, and discuss potential contributions to deer management strategies.