The effective management of traffic flows during convective weather events in congested air space requires decision support tools that can translate weather information into anticipated air traffic operational impact. In recent years, MIT Lincoln Laboratory has been maturing the Convective Weather Avoidance Model (CWAM) to correlate pilot behavior in the enroute airspace with observable weather parameters from convective weather forecast systems. This paper evaluates the adaptation of the CWAM to terminal airspace with a focus on arrival decision making. The model is trained on data from five days of terminal convective weather impacts. The performance of the model is evaluated on an independent dataset consisting of six days of convective weather over a variety of terminal areas. Model performance in different terminal areas is discussed and the sensitivity of prediction accuracy to weather forecast horizon is presented.