The Automated Real-Time Clearance Analyzer (ARCA) addresses the future safety need for Real-Time System-Wide Safety Assurance (RSSA) in aviation and progressively more trusted autonomy as will be explored in NASA's SMART-NAS and SASO within the Airspace Operations and Safety Program (AOSP). ARCA builds on recent advances in probabilistic (Bayesian) network modeling and the rapid expansion of big data capabilities. The application of ARCA that we propose to develop, ARCA-A, performs safety analyses of approach clearances based on multiple sources of relevant real-time data, such as real-time aircraft data, weather data, past and current operations data, and crew data. ARCA-A provides intelligent risk assessment of clearances over the lifetime of the operation, from planning to clearance delivery. As it matures, ARCA can play a range of roles at increasing levels of autonomy and authority. Initially, once it has trained to the level of generating insight, it can be used to identify hot spots in the NAS or in a region (specific areas, procedures, aircraft types, or times of day when risks increase) on a daily or weekly review basis. Next, it could be deployed to air traffic managers, dispatchers, or other users with real-time operational oversight. With further integration, it could optionally display real-time informational warnings on ATC displays, flight displays, or dispatcher screens. Eventually, ARCA could play a foundational role in automated clearance selection and delivery. For research purposes, in this project we propose to design and begin development of a specific ARCA-A application. The primary focus of the research will be core algorithms, information integration, performance, and feasibility. ARCA is a promising new concept that represents a major step forward in aviation safety from static, forensic, manual methods toward real-time, prognostic, automated capabilities, the end result of which will be safer and more efficient operations.