Whether clouds are composed of liquid water drops, ice crystals, or a mixture of the two impacts the hydrologic cycle, top of the atmosphere and surface radiation, and the remote sensing of cloud properties from satellites. We will present radiative transfer calculations demonstrating the potential for daytime and nighttime retrievals of cloud thermodynamic phase using high spectral resolution infrared satellite observations. These radiative transfer calculations are used to choose a set of AIRS channels for phase discrimination that maximize sensitivity to cloud phase while minimizing sensitivity to cloud particle size and atmospheric water vapor. Cloud thermodynamic phase classification using AIRS data will be demonstrated and compared with other cloud observations, including height, temperature, and cloud type, from A-Train instruments including MODIS, CALIPSO, and CloudSat.