This study presents a novel approach to simplify the dynamic life cycle assessment (DLCA) of buildings by identifying and prioritizing influential dynamic parameters (DPs) to improve building energy performance and reduce greenhouse gas emissions. Current life cycle assessment (LCA) methodologies lack temporal considerations, which can significantly impact a building's environmental footprint over its multi-decade life span. We conducted an extensive literature review on DPs in DLCA, informing the creation of a multi-scenario parametric framework. A case study was then selected to apply the developed DLCA methodology and perform a global Sensitivity Analysis to pinpoint the most influential DPs on global warming potential. The DLCA framework integrates data from the French database for environmental product declarations and utilizes EnergyPlus simulations for operational emissions assessment. The study identifies ten DPs, revealing the most impactful ones to be industry and waste sector’s emissions reductions, building occupancy, and global warming. Additionally, we found minimal interactions between DPs, which facilitates the simplification of the DLCA process. This research enables building stakeholders to focus on a more selective set of parameters, enhancing the efficiency and accuracy of building life cycle assessments. Overall, our findings contribute to the continuous improvement of LCA methodologies and promote sustainable building practices.