Climate change poses significant risks to forest productivity and resilience; as climates shift, many tree populations may become maladapted to their local environments. Assisted migration of forest trees is gaining popularity as a strategy to mitigate the potential negative effects of climate change on forests. The DIVERSE project, a pan-Canadian research initiative, aims to enhance forestry practices through strategies such as assisted migration by developing a tool to match prospective forestry sites with climate-suitable tree populations. The assisted migration tool leverages climatic data to guide foresters in selecting source populations that are resilient under current and future conditions. Current iterations of the tool have limited selection of prospective sites and have difficulty giving accurate guidance in certain regions. We aim to expand the capability of the assisted migration tool to allow input of any prospective planting site and improve it's predictive model. In order to achieve this we propose an ecozone-based climate matching approach that will simplify climate data in the tool’s database while sacrificing very little predictive power. In this study, we find ecozone-based climate matching to be a generally viable approach for assisted migration prediction models, and also identify geographic regions in coastal BC and southern Mexico where the model may need improvement. Additionally, we find that the relationships between annual climate variables are not predicted to change under near-future projections, and use principal component analysis to generate multivariate metrics that reduce the dimensionality of our climate dataset to further increase efficiency.