In Tunisia, Durum wheat (DW) holds the most important place among irrigated cereals in terms of production and cultivated area. It is grown on an average annual area of 48 700 ha, which represents two-thirds of the irrigated cereal area. This area allows producing an average of 180 000tons representing around 20% of national durum wheat production. However, the achieved yield of the durum wheat, reached 360kg/ha against an expected yield of 700 kg/ha (El Faleh and Gharbi, 2014). This result showed also very low water productivity and economic performance. Focusing on the irrigation practices, researches have shown that poor management in terms of applied dose and irrigation timing are major factors limiting the agronomic performance of the DW. Other researches have focused on the cropping system and have pointed out the negative impacts of pricing policy on the economic performance of DW and profit at regional level. In order to improve the durum wheat production and the economic performance, there is an urgent need for approaches that integrate both economic and agronomic criteria. As pointed out by many studies that bio economic modelling approach is the most widely recommended approach for studying the effect of different management practices on farm performance (Blanco and Flichman, 2002). Several bio-economic models have been developed for production at the field level and farm level (Reckling et al., 2016). However, they fail to identify impacts at higher levels (e.g., region, country) that may be useful to policy makers. Hybrid models address this issue by aggregating results from the farm level to higher levels (Britz et al., 2012). These models usually consider the diversity of farm types (e.g., crop, livestock) and technologies, but none of them focuses on cereal production. This work aims to highlight the main levers for improving the agronomic and economic performance of DW crop and the regional profit. In order to do this issue, we develop the economic model MORBIT coupled to the biophysical model CROPSYST.