PURPOSE: To improve the prediction performance of the predicting device for the time-series data.

CONSTITUTION: This device consists of a 1st time-series predicting means 12 which is structured by using a feedforward type neural network, a 2nd time- series predicting means 12 which is structured by using an ARIMA model, a use characteristic measuring means 14 which inputs use conditions 18, the prediction results 16 and 17 of the 1st and 2nd time-series predicting means 11 and 12, and an actual measurement result 19, compares the prediction results 16 and 17 with the actual measurement results 19 by the use conditions 18 to measure whether prediction ability corresponding to the use conditions 18 is inferior or superior by the time-series predicting means 11 and 12, and an integrated decision means 13 which inputs the use conditions 18, prediction results 16 and 17, and measurement result 20 of the use characteristic measuring means 14 and integrates the prediction results 16 and 17 by a weighted adding method according to the use conditions 18 and measurement result 20 to output a final prediction result 21.