Soil-crop models are widely used as valuable tools to assess the combined effects of cropping practices, soil management and climate on the agro-environmental indicators. They provide a wide range of predictive information that are useful to design and evaluate innovative cropping systems. However, intercropping modeling is still under development, especially for grain legumes-based intercropping system. We performed here the first calibration of the STICS (v 9.2) model on chickpea grown under contrasting nitrogen (N) levels during two copping seasons (2018/2019 and 2019/2020). This calibration allowed us to simulate a wide range of agronomic scenarios (climate, N-fertilization and cropping system) to optimize intercrops (durum wheat-chickpea) management. 37 parameters were estimated by using a sequential optimization method. Our results showed that STICS performs well in predicting Leaf Area Index (LAI), above ground biomass (AGB) and N uptake (AGPN) for both intercropped and sole cropped species, with satisfactory model efficiency (EF ranged from 0.62 to 0.93). In addition, grain yield was correctly predicted by the model with small error (NRMSE=13%) especially for wheat crop (EF=0.50), while it was less correctly predicted for chickpea crop (EF=0.24 and NRMSE=21%). STICS predicted well root depth under the conditions of our field study (EF = 0.65 and NRMSE = 37%). For soil outputs variables, the model simulated adequately soil water content with a satisfactory model efficiency (EF = 0.65) and low relative error (NRMSE =. 8.8%) especially for sole cropped and intercropped chickpea. The soil N stocks were less adequately predicted (EF = 0.28) with high relative error (NRMSE = 56%) in sole cropping system, while it was moderately adequately predicted (EF = 0.44) in intercropping. Under the two contrasted years and N-application conditions of this study, the temporal dynamic was well reproduced by the model for both plant and soil outputs with low simulation errors.