The chapter discusses the methods of using artificial intelligence tools in the field of technical diagnostics of defects in NPP power equipment. Special attention is paid to the principles of building diagnostic systems based on neuro-fuzzy networks such as ANFIS, using expert knowledge bases and associative rules. The concept of identifying defects in thermal mechanical equipment of nuclear power plants by the method of defect pattern recognition is proposed. The basic principles of determining the pre-emergency states of power equipment based on artificial neural networks are presented. Within the framework of the presented research, a mathematical and thermohydraulic model of a tubular heat exchanger and a neuro-fuzzy expert ANFIS system for determining heat exchanger defects based on pattern recognition have been developed. A variant of using the developed diagnostic model as part of an automated control system of an electric power plant as a system of assistance to the operator of the technological process is proposed.