The optimization of predictive maintenance relies mainly on the reduction of costs and risks, which can be of various types. The evaluation of risks cannot be realized independently of the psychology state and cognitive knowledge of the decision maker. In this article, we demonstrate this through the proposal of a methodology that tackles both optimization of maintenance and estimation of failure risks at the same time. The methodology takes as input the remaining useful life of the system at instant t and determines the optimal inspection step and the threshold of remaining useful life for predictive maintenance. The originality of the methodology consists of using a theory inspired by behavioral economics called prospect theory. Prospect theory allows modeling the outcome of a decision making by considering several aspects related to the decision maker, mainly loss aversion and a tendency to overestimate events with low probability of occurrence but with high economic losses. A case study was then developed where both cases were considered: with prospect theory and without prospect theory. A sensitivity analysis of the results under variation of some input parameters was carried out in a final step to confirm the consistency of the results and show the interest of prospect theory.