The decarbonization of existing building stock, in the context of climate change, is a relevant challenge for the coming years. Technologies to deal with the increasing occurrence of heat waves need to be explored, and the opaque ventilated facades (OVFs) could be a proper building system. The operating principle is the increase in temperature of the air within the cavity – thanks to the solar radiation – which results in a stack effect phenomenon. Therefore, heat is expelled from the cavity through the air in natural convection, reducing the temperature of the internal wall and consequently the cooling energy demand. Several design parameters – among which the cavity depth, the external coating emissivity, the dimensions of the façade’s components – and boundary conditions are needed to accurately model an OVF through a computational fluid dynamics (CFD) approach. In this study, a sensitivity analysis to investigate the effects that input, and configuration parameters have on the energy performance of an OVF is proposed, facilitating the evaluation of which input are more impactful. To this end, several CFD models are realized and examined, mainly evaluating the convective heat transfer coefficient in the cavity. The proposed investigation is relevant for the development of a tool able to estimate the energy impact of an OVF through machine learning techniques.