Reinforced concrete structures are not only subjected to mechanical loading but also continuously exposed to diverse environmental actions over their service life. These combined actions trigger a variety of interacting physico-chemical degradation mechanisms, including carbonation and chloride-induced corrosion, alkali-silica reaction, calcium leaching and sulphate attack, which collectively govern the durability and structural performance of reinforced concrete. Corrosion of reinforcement represents one of the most critical deterioration mechanisms, as it leads to cracking, spalling, and stiffness loss. Therefore corrosion is responsible for substantial economic damage and reduced sustainability due to shortened service lives and premature need for repair or replacement. Enhancing the durability and extending the service life of existing and new structures is therefore a key lever to improve the sustainability of the built environment, as it directly reduces life-cycle resource consumption and associated environmental impacts. The long-term behaviour of reinforced concrete is strongly influenced by the cement type, binder composition, and mixture design. With the increasing use of alternative and low-clinker binders to reduce CO2 emissions, the availability of empirical long-term performance data becomes limited, and traditional design rules calibrated for conventional cements may no longer be sufficient. In this context, advanced coupled thermo-hydro-chemo-mechanical (THCM) modelling provides a powerful framework to predict the long-term macrostructural behaviour of reinforced concrete structures, even when long-term field data are scarce. Such models enable a more realistic assessment of serviceability and load-bearing capacity over time, accounting for interactions between transport processes, chemical reactions, and mechanical damage. This contribution presents a Python-based computational framework for the holistic simulation of the long-term performance of reinforced concrete structures under coupled THCM actions. The framework enables the flexible integration of transport and degredation models, and their coupling with structural analysis tools. By providing a modular and extensible platform, the framework allows users to perform scenario analyses over several decades of operation, to quantify the impact of degradation processes on stress redistribution, crack development, stiffne