Most of the C and N models published over past decades are based on parameters not always linked to the environment and underestimate the role of microorganisms. They are often over-parameterized, which can give multiple solutions for flow calculations between state variables. This work proposes a modelling method centred on the functioning of living organisms in order to calculate flow parameters using data on N stocks in decomposers, plant organs, symbiotic microorganisms, and the soil compartments. The model was settled via a complex N fixing and intercropping system of durum wheat/faba bean compared to the cropping of pure durum wheat and pure faba bean, all in the context of organic farming invaded by weeds and weeded by hand just before flowering. To avoid perturbation of natural exchanges of C and N, no fertilizer was added from 1997 to 2011. The equation system defined for the association of any number of plants, as well as parameters previously published for C-flow calculations were used, and only a few parameters specific to N flows were added, and are discussed. The results showed the strong link between N and C in the environment. The calculations converge toward an unique set of solutions that is consistent with literature data when available. The labile organic N of microbial origin was modelled as the main potentially available stock. Living microorganisms stored about 1% of total N, which was close to the N stock in faba bean and four times more than stock in durum wheat. Inorganic N was immobilized before flowering in competition with N requirement of durum wheat roots. Net N mineralization, mainly from decomposition of faba bean roots, started too late to improve wheat production. During the cropping period, weeds accounted for losses of 20 kg N ha−1, while the atmospheric N2 fixation of 90 kg N ha−1 was close to the total microbial immobilization. The model associating microbial and plant flows of C and N in complex plant covers, appears as a robust tool to quantify the exchanges of the earth organisms with the soil and atmosphere. It enables to propose essential recommendations to improve as well agro-ecology as predictions of global changes of C and N stocks.