To further investigate the grain growth behavior of Inconel X-750 superalloy， artificial neural networks were employed in this work. The grain growth tests of Inconel X-750 superalloy were carried out to obtain the grain distributions under different holding temperatures and holding times， and the influences of the holding temperature and holding time on the size and non-uniformity of grains were investigated. The artificial neural network based grain growth model involving grain non-uniformity was constructed with the holding temperature and holding time as inputs， and average grain size and coefficient variation of grain size as outputs. The relationships between the grain size， grain non-uniformity， holding temperature and holding time under isothermal condition were established by predicting the grain sizes and grain non-uniformities in wide process parameter range using the constructed grain growth model. The results show that the neural network model for grain growth possesses high precision.