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The Traffic Flow Impact (TFI) Tool, from MIT Lincoln Laboratory and the Federal Aviation Administration, is a unique tool that provides air traffic control managers with a display of airspace capacity predictions and potentially achievable and sustainable traffic flow rates by using a revolutionary approach to integrate multiple weather forecasts. TFI uses a novel machine-learning technique to compute an airspace impact metric called permeability, which in simple terms is the overlap of measured storm features with an airspace resource to determine the amount of usable airspace. An established relationship between permeability and observed traffic flow rates is used to provide guidance to air traffic control managers on a potential set of traffic rates that are based upon the forecasted permeability. A machine learning approach is used to combine several deterministic and probabilistic convective weather forecast models to provide a predicted permeability and a range of potential permeability. TFI allows stakeholders to discuss appropriate Traffic Management Initiatives to efficiently handle airspace demand/capacity imbalances caused by adverse weather conditions.