In other words the modeling phase allows detecting the basic patterns governing the supply chain behavior and provides developers with the relevant conceptual model for recreating the real system essence in a synthetic environment. Therefore the ability to capture as faithfully as possible the working logics of a real fish supply chain in a simulation tool provided with predictive capabilities relies on the accuracy of the underlying model and as a consequence on capability of abstraction from irrelevant details. As for the simulation paradigm a DES approach has been adopted. DES is a discrete-state, event-driven system; this means that its state evolution depends entirely on asynchronous events occurring over time and therefore is suitable for the purpose of the study. As already said, the simulation model is devoted to recreate possible contamination phenomena. Therefore the supply chain “stationary” conditions of goods flowing along are perturbed by a certain quantity of contaminated products that can potentially affect every link of the supply chain; therefore the model is stochastic in nature and includes stochastic variables. One of them is the probability of contamination for each link, indicated as Pj where j identifies the corresponding supply chain link. During the time interval between the contamination event occurs and the company becomes aware of it, contaminated food continues moving along the supply chain toward the shelves that will be reached in a given time, depending on the supply chain structure (i.e. number of links, frequency of orders, quantity of stock in the chain).