The Air Force Weather Agency (AFWA) has been continuously operating a satellite-based, global cloud analysis model since 1970. Periodic enhancements to the processing software and algorithms have resulted in a transition from reliance on polar-orbiting environmental satellites alone to, most recently, a mix of six polar and five geostationary satellites. Polar Regions have long presented a significant challenge due to the unique surface and solar illumination conditions that can make discrimination of clouds from the background problematic. In the latest version of the AFWA model, analysis of low and mid latitude regions is heavily weighted toward use of geostationary data due, primarily, to their high refresh rates. This has allowed a new focus on use of polar-orbiting data to more accurately characterize the Polar Region clouds. Currently the operational model is undergoing an update to implement a new series of algorithms designed specifically to improve performance in Polar Regions. Since the AFWA model is part of an operational system, it is not currently using data from the experimental MODIS sensors, thus the new techniques are designed to operate with the AVHRR-3 sensor, operating in either a channel 3 a/b switching mode or a fixed channel 3 b mode. Specific features include use of temporal information to identify transient cloud features such as those that form around opening/closing leads, multispectral techniques to identify black stratus cloud (i.e., clouds that form below intense surface inversions and that are warmer than the background surface) that often form over elevated Antarctic surfaces during the extended polar night, and decision tree algorithms to identify conditions where the surface temperature is much lower than predicted due to extreme radiational cooling. Representative samples of real-data retrievals illustrating algorithm performance under varying conditions will be presented along with a discussion of the process being employed to transition the new algorithms from research to operations.