Health Index is a practical tool that determines the priorities for investment, field studies, combining the results of field and laboratory tests represents for asset management, capital and maintenance plans, operating observations. In this study, transformer health index predicted using artificial neural network and test results of various types of transformers. The main purpose of this study is to develop a reliable health index for transformers. The suggested transformer health index calculation method will allow optimum transformer life prediction and assess the transformer health. The results show that the comparison between the actual transformer health index and the estimated one based on real time data is acceptable around 80% similarity rate.