Predicting engineering properties of materials prior to their synthesis enables the integration of their design into the overall engineering process. In this context, the present article discusses the foundation and requirements of software platforms for predicting materials properties through modeling and simulation at the electronic, atomistic, and mesoscopic levels, addressing functionality, verification, validation, robustness, ease of use, interoperability, support, and related criteria. Based on these requirements, an assessment is made of the current state revealing two critical points in the large-scale industrial deployment of atomistic modeling, namely (i) the ability to describe multicomponent systems and to compute their structural and functional properties with sufficient accuracy and (ii) the expertise needed for translating complex engineering problems into viable modeling strategies and deriving results of direct value for the engineering process. Progress with these challenges is undeniable, as illustrated here by examples from structural and functional materials including metal alloys, polymers, battery materials, and fluids. Perspectives on the evolution of modeling software platforms show the need for fundamental research to improve the predictive power of models as well as coordination and support actions to accelerate industrial deployment.