Farmed Atlantic salmon is an important dietary source of long-chain n-3 polyunsaturated fatty acids, particularly eicosapentaenoic acid and docosahexaenoic acid. As a result, fillet fatty acid composition directly relevant to product quality and nutritional value for consumers (1). The fatty acid profile of salmon fillet is shaped by dietary fatty acid supply, as well as environmental and management drivers that influence fatty acid metabolism and deposition. Current predictive approaches focus only on dietary input, and primarily represent dietary change as the dilution of the initial tissue lipid pool by newly deposited dietary lipid (2). These approaches provide limited representation of external drivers and the underlying biological processes. In this study, we developed a process-based model to track fish growth and fatty acid dynamics by explicitly representing digestion and absorption, bioconversion to longer and more unsaturated fatty acids, tissue deposition, and β-oxidation, while accounting for environmental and management factors. Data extracted from published feeding trials and first-hand experimental studies were compiled into separate calibration and validation datasets. Model parameters were estimated using bounded multi-start nonlinear least squares with centred log-ratio residuals and study-balanced weighting. The process-based model produced a root mean square error of 1.16 percentage points and R² = 0.947, compared with 1.41 percentage points and R² = 0.921 for the dilution model. The reduction in prediction error was larger under non-optimal scenarios (1.13 vs 1.50 percentage points) than under optimal conditions (1.19 vs 1.32 percentage points). Overall, the process-based model achieved comparable predictive accuracy to the dilution model under optimal conditions, while demonstrating greater robustness under non-optimal conditions. These results demonstrate the value of explicitly representing the biological processes governing fatty acid fate rather than relying solely on dietary dilution. Further refinement of the process-based model is currently underway to better mechanistically represent fish growth processes and the underlying effects of rearing conditions on fatty acid dynamics, with greater predictive gains over existing empirical models expected. As such, the model will be a useful tool to understand and predict fatty acid composition across variable aquaculture conditions and could support the development of feeding and management strategies aimed at maintaining the nutritional quality of farmed Atlantic salmon.