Abstract: A plant malfunction diagnostic method is characterized by determining by simulation a change in a plant state variable, forming a pattern among plant state variables obtained by autoregressive analysis of the change in plant state variable, inserting the formed pattern among the plant state variables in a neural network, performing learning until a preset precision is obtained, and identifying the cause of the malfunction by inserting, in the neural network, a pattern which indicates the pattern among plant state variables formed by data gathered from the plant. This makes possible early identification of the cause of a malfunction. Plant rate of operation and safety are improved by allowing the operator to perform the appropriate recovery operation with a sufficient time margin.