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The paper presents an innovative approach for the damage assessment of ductile cast irons (DCIs) by using a probabilistic-based methodology. The study is based on the experimental results of acoustic emissions (AEs) tests performed on pearlitic DCIs subjected to both monotonic and fatigue tensile loading. The information entropy of the AEs data is confirmed to be well correlated to both the damage progress and the occurrence of the incipient failure. Robust failure criteria are finally provided for real-time assessment in structural health monitoring applications.