Transformers play a big role in the distribution of electrical energy. One of the factors that determines the reliability level of the transformer is the life of the transformer. If the transformer is used longer, the level reliability of its transformer will be decrease. The purpose of this research was to predict the life of a transformer based on the health index transformer calculation, then the value of health index transformer will be modeled by using artificial neural network. The results of this research were the values used as the parameters in transformer testing, which were insulating oil, furan, and dissolved gas. One of the advantages of artificial neural network methods in predicting the life of the transformer is a calculation error that can be minimized. From the result of this research, the transformer's life prediction system can be used directly to determine the lives of other transformers, both new and operating ones, with a low percentage of errors. Furthermore, this method can be used as an option in maintaining power transformers.