Sedimentary forward numerical modeling is a key method to study depositional processes supported by numerous numerical models. However，the model selection and application are difficult. This review summarized model features，including sedimentary time scales，driving mechanism，channel evolution，following rules，sedimentary outcomes，and applicable objects. The mathematical principles，parameter selection，simulation outcomes and restrictions of Delft3D and DIONISOS are illustrated as well. It shows that the sequence evolution controlled by lake level change hierarchy correspond to the sedimentary scales. Combining the characteristics of sediment components and simulation objectives is the basic principle of optimizing the numerical model. The well-seismic data and geological modeling algorithm are the necessary means to verify and optimize the training model. The deep-learning and reinforcement-learning numerical models based on big data and AI are main trends for sedimentary forward numerical modeling.