The significance of sustainability has steadily increased over the last decade, driving industries to explore innovative approaches that mitigate environmental impact while maintaining operational efficiency. Additive Manufacturing (AM) has emerged as a promising solution, offering design flexibility and potential for resource efficiency and localized production. However, accurately assessing the environmental impact within AM process workflows remains challenging, particularly within a life cycle assessment (LCA) context. This paper aims to address this gap by introducing a method to estimate energy consumption in Material Extrusion (MEX) AM and integrate it in the main workflow of the process. The study analyzes two different 3D printers and quantifies the energy contributions of different machine components across various operational conditions. Additionally, it describes regression models with high performance in predicting energy consumption based on key printing parameters such as printing time, nozzle temperature, and building plate temperature. This research contributes to advancing our understanding of energy efficiency in AM processes and supports the integration of sustainability considerations into additive manufacturing workflows. The findings have implications for optimizing energy usage, minimizing environmental impact, and enhancing the overall sustainability of AM operations.