The nutritional value of feed ingredients for pigs is known to be affected by the kinetics of nutrient digestion, which in turn is affected by diet × animal interactions. Although current feed evaluation systems provide invaluable tabular values regarding the chemical composition and nutrient digestibility of feedstuffs, interactions between ingredients and between the diet and animal are not accounted for in predicted nutritional values. To aid future predictions of the nutritional value of diets and feed ingredients, an in-silico nutrient-based mechanistic digestion model (SNAPIG) was developed. The model comprises 48 pools representing gastrointestinal protein, starch, fat, non-starch polysaccharide, their hydrolysis products, endogenous secretions, and microbial biomass. Nutrient hydrolysis kinetics vary with feed ingredient origin, and parameters were estimated from in vitro assay data. Feed protein, starch, and fat were differentiated in (enzymatically) degradable and undegradable fractions and specific hydrolysis rates were estimated according to their feed ingredient origin. Based on in vivo studies, passage of digesta solids and liquids from the stomach was modelled as a function of nutrient solubility and by diet viscosity, diet solubility, and feed intake. 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.