Satellite-based estimates of precipitation are an important part of precipitation monitoring over the Americas due to their high resolution in both time and in space, as well as their continuous spatial coverage over mountainous regions and oceans. Several algorithms for retrieving quantitative precipitation estimates (QPE) from satellite data have been developed by scientists at the NOAA/NESDIS Office of Research and Applications (ORA), some in collaboration with other researchers. Several of these algorithms are described, including the Auto-Estimator (AE), Hydro-Estimator (HE), GOES Multi-Spectral Rainfall Algorithm (GMSRA), and a technique that uses microwave-based estimates of rainfall rate to recalibrate an AE-like algorithm. Each of these algorithms approaches satellite QPE from a slightly different angle, resulting in differing strengths and weaknesses for each algorithm. In addition to an overview of each algorithm, validation results from the first year of intercomparison in the ORA Satellite QPE Validation Program are presented, and future directions for research and algorithm development are discussed.