Modelling approaches help clarify how the structural organization of meat influences digestion, nutrient release and overall nutritional quality. Statistical and machine-learning tools support the prediction of key matrix-related traits such as composition, texture or digestibility, by capturing complex relationships within experimental datasets. In parallel, mechanistic models provide a more detailed representation of heat and mass transfer phenomena and digestive processes, integrating the heterogeneous structure of meat particles with the dynamic conditions of the gastrointestinal environment.