The quality and safety of a cooked food product depends on many variables, including the cooking method and time–temperature combinations employed. The overall heating profile of the food can be useful in predicting the quality changes and microbial inactivation occurring during cooking. Mathematical modeling can be used to attain the complex heating profile of a food product during cooking. Studies were performed to monitor the product heating profile during the baking and boiling of shrimp and the baking and pan-frying of salmon. Product color, texture, moisture content, mass loss, and pressed juice were evaluated during the cooking processes as the products reached the internal temperature recommended by the FDA. Studies were also performed on the inactivation of Salmonella cocktails in shrimp and salmon. To effectively predict inactivation during cooking, the Bigelow, Fermi distribution, and Weibull distribution models were applied to the Salmonella thermal inactivation data. Minimum cooking temperatures necessary to destroy Salmonella in shrimp and salmon were determined. The heating profiles of the 2 products were modeled using the finite difference method. Temperature data directly from the modeled heating profiles were then used in the kinetic modeling of quality change and Salmonella inactivation during cooking. The optimum cooking times for a 3-log reduction of Salmonella and maintaining 95% of quality attributes are 100, 233, 159, 378, 1132, and 399 s for boiling extra jumbo shrimp, baking extra jumbo shrimp, boiling colossal shrimp, baking colossal shrimp, baking Atlantic salmon, and pan frying Atlantic Salmon, respectively.