Atlantic salmon is characterized by highly acceptable sensory qualities and a nutritional composition rich in fatty acids. However, food processing procedures, including improper heat treatment, can lead to unfavorable changes in quality and nutritional value. In this study, a computational fluid dynamics computer simulation was used to model the quality attributes of the roasted salmon product by controlling input parameters such as temperature, humidity, and air movement speed. Including the degree of denaturation of myosin, collagen, sarcoplasmic proteins, and actin, as well as docosahexaenoic acid decomposition and weight loss. Based on the conducted simulations, a prediction model was developed using the response surface methodology. According to the optimized model, salmon samples should undergo processing at a temperature of 151.38 ℃, with 20% humidity, and the fan speed set to 452.78 RPM. After the optimized heat treatment process, the degree of denaturation of salmon proteins was as follows: myosin denaturation at 95.12 ± 1.35%, collagen denaturation at 84.97 ± 1.72%, sarcoplasmic proteins denaturation at 37.71 ± 1.52%, and actin denaturation at 16.43 ± 0.71%. Furthermore, the weight loss was measured at 17.88 ± 0.55%, and docosahexaenoic acid decomposition at 0.56 ± 0.07%. This innovative hybrid method, using computational fluid dynamics and response surface methodology, for forecasting and optimization, can be applied to model thermal processes in the food industry. [ABSTRACT FROM AUTHOR]