###### Abstract  
This study aimed to calculate the optimal thermal processing parameters for goose meat using CFD simulation. CFD provides a precise determination of heat treatment conditions by predicting protein denaturation and mass loss, leading to higher quality and improved sensory experience and, thus, acceptance of products. Accurate calculation of these conditions reduces energy losses and enhances process efficiency in the food industry. This study focused on the prediction of protein denaturation and cooking loss in goose breast meat during roasting. Specific CFD techniques, including conjugate heat transfer and phase change models, were utilized to ensure accuracy in protein denaturation prediction. These models accounted for variations in meat composition, such as fat and water content across different samples, which improved the accuracy of the predictions. Optimal conditions were determined using a mathematical model. These conditions were 164.65 \({}^{\circ}\)C, 63.58% humidity, and a fan rotation of 16.59 rpm for 2000 s. The myosin, collagen, and actin denaturation levels, as well as cooking loss, closely matched predicted values. The findings show that CFD is a valuable method for evaluating protein denaturation and cooking loss in goose breast meat, potentially improving product quality and consistency in gastronomy and the meat industry. This innovative optimization method enhances food production efficiency and elevates sensory characteristics, physicochemical properties, and nutritional value, contributing to consumer satisfaction and market competitiveness. The model proposed in this paper can be adapted to predict denaturation in other types of meat or food products with necessary modifications, offering broad applicability. Potential limitations of using CFD in protein denaturation prediction in complex food matrices include the need for detailed compositional data and computational resources, which can be addressed in future research. content in goose meat result in dynamic thermal transfer to the geometric interior of the sample. Additionally, the unique muscle structure of geese, which contains more dark muscles rich in myoglobin, can affect the rate and manner in which proteins denature. As a result, goose meat may require a longer cooking time compared to poultry or pork to achieve optimal texture and flavor. Goose meat, with its unique texture and flavor, is gaining popularity [2; 3]. Meeting these consumer expectations requires not only excellent breeding and nutrition but also a precise understanding of the processes influencing the final product's quality [4]. The quality of goose meat thus becomes a key competitive factor in the food market, affecting not only health but also overall consumer satisfaction [5; 6; 7]. A critical aspect of goose meat quality is the protein denaturation process, which is a complex phenomenon involving dynamic processes at the molecular level that largely determine the final structure and characteristics of meat products [8; 9]. This is a key process in shaping the unique characteristics of goose meat, affecting its cohesion, juiciness, and durability [10; 11]. Understanding the correlation between thermal process parameters and protein denaturation in goose meat can provide valuable insights into optimizing these parameters to achieve the desired balance between meat durability and preserving its taste, consistency, and nutritional value [12; 13; 14]. To meet the growing expectations of consumers and improve the energy efficiency of meat production, strict control and optimization of thermal process parameters are essential [15]. Parameters such as temperature, process duration, and heat flow velocity are crucial in minimizing energy and resource losses while aligning with sustainable development principles [16]. Furthermore, optimizing these thermal parameters directly impacts the sensory characteristics of goose meat, influencing the taste, aroma, and consistency of the meat.