Mediterranean mussels (Mytilus galloprovincialis) are filter feeders that can accumulate bacteria, including Escherichia coli, presenting potential health risks. This study assesses the microbiological safety of mussels from offshore farms in Cala Iris Bay, Northern Morocco. The objectives were to evaluate E. coli levels and detect Salmonella in mussels, ensure compliance with Moroccan sanitary regulations, and develop a predictive model for E. coli survival to inform management decisions. A total of 72 mussel samples were collected from three stations in Cala Iris Bay over a 12-month period, covering all seasons. Standard microbiological methods were used to enumerate E. coli and detect Salmonella. Two models, the classical primary model and the Weibull model, were used to predict E. coli survival. Model performance was evaluated using root mean square error (RMSE), adjusted correlation coefficient (R2 adj), and Akaike Information Criterion (AIC). 80.5% of the samples met the safety standards defined by Moroccan Circular Number 1508/12, while 19.5% required further treatment. The Weibull model provided a more accurate prediction of E. coli survival compared to the classical primary model. The study underscores the necessity of continuous monitoring and effective modeling in ensuring the microbiological safety of mussels. The Weibull model proved to be a valuable tool for predicting E. coli survival, aiding in the management of aquaculture practices. This research contributes to the broader field of food safety and aquaculture management, offering insights that can guide decision-making and enhance public health standards in seafood production.