The potential interest of a dynamic crop model is to provide reliable predictions of oil concentration (OC) soon before harvest as well as helping to understand at which time oil dynamics was affected by environmental stresses or management. For that pm·pose, we proposed a "source-sink" based dynamic model describing on a daily step nitrogen and carbon assimilations and remobilizations during sunflower grain filling. Priority rules were established for C and N depletion from "source" organs, as well as for their allocation into "sink" organs. Photosynthesis was simulated using the radiation use efficiency approach and nitrogen uptake according to Pan et al. (2006) fonnalisms. Water and N stresses were computed by SUNFLO crop model from climatic and soil data find genotype characteristics. The "source" and "sink" variables were initialized at flowering and main outputs were oil and protein concentrations and weights per m2 . The model was calibrated on 24 crop situations in 2012 and evaluated independently on 50 other situations (3 years) with contrasted genotypes and environments. Global trends were well reproduced for all "source" and "sink" components but most variables tended to be overestimated. The main indicators of model quality for predicting OC were: RMSE = 6.1 (%), efficiency = 0.97, R2 = 0.94 and Bias = -0.06 (%). A sensitivity analysis suggested us to reduce the number of parameters, better describe photosynthesis and N uptake processes, and improve the parameterization of genotype and nitrogen effects in order to decrease the prediction error and provide a relevant tool for OC prediction.