The ash fusion characteristics and viscosity-temperature characteristics of coal are the two indexes parameters for the dischargeof the molten slag in the entrained flow bed (EFB). The chemical reaction in EFB gasifier is under harsh conditions of high temperature,high pressure, and turbulent with multiple phase reactions, and it is difficult to obtain the molten slag fluidity behavior parameters by experience, and establishing a model that predicts these parameters is of vital importance. Based on the analysis of ash melting characteristicparameters (ash melting temperature, full liquid phase temperature), viscosity temperature characteristic parameters (viscosity, criticalviscosity temperature) and influencing parameter factors, the prediction principles and steps of four methods: regression analysis, softwareprediction (FactSage, LAMMPS), mathematical modeling (backpropagation neural network, support vector machine) and ion potentialprediction method were expounded, and the prediction model for the construction of ash fusion characteristic parameters and viscosity-temperature characteristic parameters was systematically reviewed. Finally, the advantages, disadvantages and application scope of thefour methods for predicting coal ash flow behavior were summarized. Based on the composition of coal ash and its microstructure,combinedwith thermodynamic and kinetic simulation software, the mathematical model was used to optimize a the flow parameters. So as to establishthe optimal prediction formula, which is of great significance to guide the accurate prediction of molten slag fluidity behavior in theEFB gasification process.