Body tissues are generally N-15-enriched over the diet, with a discrimination factor (Delta N-15) that varies among tissues and individuals as a function of their nutritional and physiopathological condition. However, both N-15 bioaccumulation and intra-and inter-individual D N-15 variations are still poorly understood, so that theoretical models are required to understand their underlying mechanisms. Using experimental D N-15 measurements in rats, we developed a multi-compartmental model that provides the first detailed representation of the complex functioning of the body's D N-15 system, by explicitly linking the sizes and D N-15 values of 21 nitrogen pools to the rates and isotope effects of 49 nitrogen metabolic fluxes. We have shown that (i) besides urea production, several metabolic pathways (e.g., protein synthesis, amino acid intracellular metabolism, urea recycling and intestinal absorption or secretion) are most probably associated with isotope fractionation and together contribute to N-15 accumulation in tissues, (ii) the D N-15 of a tissue at steady-state is not affected by variations of its P turnover rate, but can vary according to the relative orientation of tissue free amino acids towards oxidation vs. protein synthesis, (iii) at the whole-body level, D N-15 variations result from variations in the body partitioning of nitrogen fluxes (e.g., urea production, urea recycling and amino acid exchanges), with or without changes in nitrogen balance, (iv) any deviation from the optimal amino acid intake, in terms of both quality and quantity, causes a global rise in tissue D N-15, and (v) D N-15 variations differ between tissues depending on the metabolic changes involved, which can therefore be identified using simultaneous multi-tissue D N-15 measurements. This work provides proof of concept that D N-15 measurements constitute a new promising tool to investigate how metabolic fluxes are nutritionally or physiopathologically reorganized or altered. The existence of such natural and interpretable isotopic biomarkers promises interesting applications in nutrition and health.