A new algorithm for retrieving volcanic ash cloud height from satellite-based measurements is presented. This algorithm, which was developed in preparation for China's next generation meteorological satellite (FY-4), is based on volcanic ash micro-physical property simulation and statistical optimal estimation theory. The MSG satellite's main payload, a 12 channel Spinning Enhanced Visible and Infrared Imager (SEVIRI), was used as proxy data to test this new algorithm. A series of eruptions of Iceland's Eyjafjallajökull volcano during April to May, 2010 and the Puyehue-Cordón Caulle volcanic complex (PCCVC) eruption in the Chilean Andes on June 16, 2011 were selected as two typical cases for evaluating the algorithm under various meteorological backgrounds. Independent volcanic ash simulation training samples and satellite based Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data were used as validation data. It is demonstrated that the statistically based volcanic ash height algorithm is able to rapidly retrieve volcanic ash heights, globally. The retrieved ash heights show comparable accuracy with both independent training data and the Lidar measurements, which is consistent with previous studies. However, under complicated background, with multi layers in vertical scale, underlying stratus clouds tend to have detrimental effects on the final retrieval accuracy. This is an unresolved problem, like many other previously published methods using passive satellite sensors. Compared with previous studies, the FY-4 ash height algorithm is independent of simultaneous atmospheric profiles, providing a flexible way to estimate volcanic ash height using passive satellite infrared measurements.