A method for predicting life of a rotary machine used in a manufacturing apparatus, includes: determining a starting time of an abnormal condition just before a failure of a monitor rotary machine used in a monitor manufacturing process, from monitor time-series data for characteristics of the monitor rotary machine, statistically analyzing the monitor time-series data, and finding a value for the characteristics at the starting time of the abnormal condition as a threshold of the abnormal condition; measuring diagnosis time-series data for the characteristic of a motor current of a diagnosis rotary machine during a manufacturing process; preparing diagnosis data from the diagnosis time-series data; and determining a time for the diagnosis data exceeding the threshold as the life of the diagnosis rotary machine.