Simulation based practises enable reducing tests and the associated cost. They can be a key driver to improve design complexity and variability and to explore new design and solutions. Eventually, simulation can be more realistic that the test. Therefore, there is a need to increase simulation credibility, in particular for composite materials. For more than 20 years, researchers have been developing advanced modelling approaches to predict the damage and failure of composite materials. Implementing such advanced constitutive models into industrial design and certification processes has not been achieved yet. Not only the complexity of such models, inherent to the physical phenomena involved, but also the lack of maturity assessment framework and standardised analysis protocols are the issues to be solved. IRT Saint Exupéry, Airbus and academic partners – ONERA, Inst. Clément Ader, Universities of Porto and Girona – are working together to develop the methods and tools to bring objective evidence of simulation credibility and enable simulation-driven certification of composite structures. A software solution called VIMS is being developed to ensure a robust and reliable use of modelling and simulation (M&S) techniques and generate material allowables. VIMS offers a framework to integrate, evaluate and use advanced composites models in association with experimental data post-processing, decision-making support and an innovation-friendly environment that facilitates the deployment within design offices. Key enablers are tackled such as verification and validation (V&V) processes and quantification and management of uncertainties (UQ&M) for reliable prediction of damage and failure of composites. Within this collaboration, models of coupon tests, such plain strength, open hole and filled hole tests, have been developed then integrated into VIMS. Manufacturing defects, such as gaps and overlaps generated by the AFP (Automated Fibre Placement) process have been studied and included in the models. Models can be analytical, based on FE (Finite Element) or based on AI algorithms. Further work includes, for instance, the implementation of a robust stochastic calibration process, the definition of validation metrics when considering a comparison between simulation results and richly instrumented tests (including digital image correlation, temperature fields, etc) and the change of scale – from coupons to structures.