While feeding tables present the chemical composition and extent of digestibility of feed ingredients for pigs, actual digestibility values depend on the kinetics of nutrient passage and digestion. Furthermore, the kinetics of these processes are also affected by diet and animal interactions. Accounting for these interactions will aid future predictions of the nutritional value of diets and feed ingredients. Therefore, an in silico nutrient-based mechanistic digestion model (SNAPIG) was developed, to predict the kinetics of nutrient digestion and absorption in the gastrointestinal tract of pigs. The model comprises 48 pools representing post-ingested protein, starch, fat, non-starch polysaccharides, their hydrolysis products, endogenous secretions, and microbial biomass. Concurrent fluxes in various anatomical compartments of the digestive tract are based on solubilization and hydrolysis kinetics of nutrients, physico-chemical properties of feed ingredients (determined in vitro), passage of digesta fractions based on mass-action approach (determined in vivo), and appearance of absorbable nutrients. Results were evaluated using observational data from nutrient absorption studies using (portal) blood in pigs (12 studies, 32 dietary treatments). Model predictions for the time of peak (44±15 v. 56±20 min after meal) and extent (69±30 v. 63±20% of intake) of glucose absorption after a meal were adequate (RMSPE=39%). For amino acids, the mean, but not the variation in time of peak could be predicted (61±11 v. 58±34 min, RMSPE=60%). The extent of amino acid absorption, based on ileal protein digestibility, was slightly over-predicted (70±5 v. 78±5%, RMSPE=12%) but variation among diets and ingredients was well predicted. Overall, the results show that SNAPIG is able to predict nutrient digestion kinetics in pigs fed diets varying in feed ingredient composition and physicochemical properties. SNAPIG’s use enables to identify knowledge gaps in pig nutrition and physiology. As such, it is a promising tool for researchers and nutritionists to improve future pig feed evaluation.