The deterioration of organic anticorrosive coating systems not only diminishes the lifetime of underlying metals but also incurs substantial economic losses and the risk of unforeseen catastrophes. Thus, rigorously monitoring and accurately predicting the lifetime of organic anticorrosive coatings are crucial. In this paper, we introduce a new approach for monitoring the electrochemical performance and predicting the durability of organic coatings. Initially, we propose a model grounded in degradation mechanisms that merges an aging kinetic model of the coating with the three-phase Wiener process, accurately representing the degradation trajectory and its inherent uncertainties. We then apply change point detection techniques, utilizing the t distribution test and the Schwarz Information Criterion, to delineate the three distinct phases of coating degradation. By defining new failure criteria based on degradation thresholds and stages, we develop a reliability model for coating systems and apply the Fiducial Inference-Monte Carlo method for numerical solutions and interval estimations. To corroborate the efficacy of our methodology, we designed electrochemical sensors for coatings and executed accelerated degradation experiments in the laboratory. The model parameters derived from the initial three sets of test data successfully predict the behavior of the fourth data set, verifying the effectiveness of the proposed method.