Abstract: Objective In accurately predicting the microstructure and properties of evaporator small nozzle after temper bead welding repair and assist in formulating the repair processes. Methods A general-purpose plug-in for temper bead welding data processing and prediction visualization was developed through Python programming based on Abaqus software. The plug-in not only simplifies the construction and management of neural network prediction models for the microstructure and properties of temper bead welding, but also enables the prediction of their microstructure and properties based on the temperature field simulation results of the temper bead welding process. Results The comparison results show that the simulated molten pool morphology is in good agreement with the macroscopic morphology of the weld cross-section. The prediction results of microstructure and hardness are in good agreement with the results of the surfacing experiment. This indicates that the temper bead welding data processing and prediction system has high accuracy and can be used for predicting the microstructure and properties of temper bead welding. The plug-in was further applied to simulate the excavation-repair process and predict the microstructure and hardness of evaporator small nozzle. The effect of interlayer grinding on the microstructure and properties of temper bead welding was analyzed. Conclusion The research results have important guiding significance for formulating the repair process of evaporator small nozzle.