On a daily basis, airport managers manually analyze current and future weather conditions to determine whether their facility will be negatively impacted. While not the only weather factor, one of the more important factors is wind, specifically wind shifts. Every morning the runway configuration for an airport is set based on the expected dominant wind flow across the area in order to maximize the efficiency of the terminal area. If the wind does not change direction over the course of the day, the airport is able operate at its optimum level, barring any other impactful weather event. If the wind does shift its direction, a change in the airport's runway configuration is required. This decision of when to change the runway configuration, however, is not always easy, and often times it can be a difficult and sometimes costly one. If the configuration of the runway is changed too late or too early in relation to the time of the wind shift, the throughput at the airport will decrease. To support this decision, a wind shift detection model is proposed. This model will utilize operational weather products, including the Localized Aviation MOS Product (LAMP) and the High Resolution Rapid Refresh (HRRR), to produce a probabilistic estimate of when a wind shift is expected to occur. By automating the process of detecting wind shifts, it improves the efficiency of the airport by allowing airport managers to focus on configuring the airport rather than when the wind shift will occur. To determine the accuracy and feasibility of the model for use in real-time operations, it will be tested at number of airports around the NAS, specifically for historical scenarios when an unexpected wind shift negatively impacted operations. Phase II will look at adding a live weather data feed to the, incorporating traffic data, as well as integrating the model within the Airport Runway Configuration Management (ARCM) concept.