Forecasters at NOAA’s Weather Prediction Center (WPC) are responsible for producing Excessive Rainfall Outlooks, which brings awareness to the potential for flood-inducing rains up to three days in advance. However, the amount of rain that qualifies as “excessive” varies from region to region, and pinpointing the specific areas likely to receive heavy rain is challenging, especially during the summer thunderstorm season. Through support from the Joint Technology Transfer Initiative, researchers from Colorado State University developed a forecast system that uses past forecasts and observations of heavy rainfall, along with machine learning algorithms, to identify the probability of flood-producing rains across the US at forecast lead times of 2-3 days. Close collaboration between the CSU scientists and WPC staff allowed for this forecast system to be transitioned into operational use, so that WPC forecasters now have an additional tool to bring awareness to areas that are at risk of potentially destructive and deadly heavy rain and flooding.