Airspace encounter models, providing a statistical representation of geometries and aircraft behavior during a close encounter, are required to estimate the safety and robustness of collision avoidance systems. Prior encounter models, developed to certify the Traffic Alert and Collision Avoidance System, have been limited in their ability to capture important characteristics of encounters as revealed by recorded surveillance data, do not capture the current mix of aircraft types or noncooperative aircraft, and do not represent more recent airspace procedures. This paper describes a methodology for encounter model construction based on a Bayesian statistical framework connected to an extensive set of national radar data. In addition, this paper provides examples of using several such high-fidelity models to evaluate the safety of collision avoidance systems for manned and unmanned aircraft.