The escalating wildfire risks in Southern California Edison's (SCE) service area require proactive strategies to safeguard infrastructure, ensure public safety, and minimize disruptions to energy distribution. This collaborative project between CIRES scientists and SCE stakeholders aims to enhance SCE's preparedness and response capabilities. Key objectives include identifying high-risk areas prone to wildfires, improving communication and coordination among stakeholders, and implementing a model for monitoring and early warning, particularly regarding vegetation life cycle and accumulation of potentially flammable vegetation. The project involves assessing historical wildfire data and infrastructure risks and developing a custom algorithm to capture vegetation life cycle using satellite data, geospatial, and machine learning tools to produce a Bayesian predictive model for estimating the buildup of potentially flammable vegetation. This project demonstrates a collaborative strategy between CIRES scientists and industry partners to achieve project goals.