Vermont's mountains are nearly fully covered in a mix of broad-leaf and needle-leaf trees whose impact on snowpack accumulation and melting is understudied. Snowfall is strongly driven by elevation and meteorological events but is secondarily impacted by forest canopy, although it is largely unknown to what extent. By controlling for elevation and weather-based differences in changes to snowpack depth at numerous monitoring stations around Vermont's highest peak, this work aims to make connections between forest canopy and snowpack dynamics. Daily snow depth measurements come from the University of Vermont's Summit to Shore Environmental Observation Network and forest canopy structure metrics are derived from both LiDAR data and aerial photography from the state of Vermont. By using machine learning algorithms, complex relationships between the two sets of variables can be determined and further studied.