Abstract: A predictive method that uses satellite-based nighttime light (NTL) observations as a proxy for power outage data that occurred during a hurricane. The NTL data is provided to a machine learning module along with exploratory variables. The module forecasts hurricane-induced power loss based on the NTL and exploratory variables. The method does not require any data from the utility, making it useful for isolated regions or regions with limited power outage records.