Abstract: Sediment forecast is the premise of real-time operation of reservoir sediment, and the complexity of water-sediment action mechanism and evolution law makes it difficult to carry out efficient and accurate sediment forecast.Based on the Azure AutoML automatic machine learning technology released by Microsoft in 2018,the construction and application of sediment prediction model were explored.The important sediment control stations along the Three Gorges Reservoir, Cuntan, Qingxichang, Wanxian and Huanglingmiao Station were selected to construct a sediment concentration prediction model, and the analysis was carried out from the perspectives of model construction and evaluation, prediction accuracy and importance of input factors.The results showed that the Azure AutoML technology can be used to construct the automatic machine learning model conveniently.The model constructed by this technology with a forecast period of 1～3 days has better prediction effect for the sediment peak regression stage and the small sediment concentration stage.While the proposed model with a forecast period of 1～2 days can carry out more accurate prediction of sediment peaks.The sediment concentration of Cuntan Station and Qingxichang Station is mainly affected by the upstream sand, while the sediment concentration of Wanxian and Huanglingmiao stations has strong autocorrelation.