Aircraft icing is one of the most dangerous weather conditions for general aviation. Currently, model forecasts and pilot reports (PIREPS) constitute much of the database available to pilots for assessing the icing conditions in a particular area. Such data are often uncertain or sparsely available. A novel method for determining flight icing conditions from satellite data has been developed for application to current GOES satellites. The prototype algorithm is physically based, relying on the determination of satellite-derived cloud parameters and thus also applicable to MODIS and SEVIRI data. A description of the prototype algorithm, validation activities, and plans for application to GOES-R will be presented. This effort will provide improvements in the temporal and areal coverage of icing diagnoses and prognoses and will mark a substantial enhancement in aviation safety in regions susceptible to heavy super-cooled liquid water clouds.