Reliable LCA background databases are essential for conducting robust environmental impact assessments. Brightway is one of the most flexible tools for performing LCA, yet it primarily relies on the ecoinvent database, making compatibility with other commercial datasets challenging. Consequently, the transparent integration of multiple background databases—such as ecoinvent, Agribalyse, or the World Food Database—has not been systematically addressed. In this work we present a Python-based workflow that streamlines the import and harmonization of LCA databases from SimaPro CSV files into the Brightway framework. The workflow was tested with three commercial food databases—Agribalyse, Agri-footprint, and the World Food Database—demonstrating two key benefits that remained unsolved up to now: (i) the incorporation of biosphere flows and its characterization factors that hindered environmental impacts of many agri-food products, and (ii) the consistent combination of different databases to ensure that the latest versions of ecoinvent datasets are used seamlessly. By expanding modeling capabilities in Brightway, improving data consistency, and enabling transparent database integration, this workflow enhances the reliability of LCA analyses and supports more robust environmental impact assessments in the food sector and beyond.