The aim of this paper is to describe the adaptation process of the LCA methodology under a modular approach (LCI data and LCIA data based on modules) in parallel to a reconfigurable design (reconfigurable manufacturing system) that enables a faster and easier quantified environmental claim for a range of milling machines. Methods: Life cycle assessment (LCA) is identified as a proper tool to evaluate potential impacts of products over the environment. However, the compilation of LCA data from one or a range of milling machines could be difficult and tedious, because, firstly they are complex products, secondly the final results have to ensure a good representability and, finally, render the assessment process cost-effectively. The analysis was performed following a cradle-to-use approach. The LCA study was performed in compliance with [18] V2.0 developed in framework of the EPD® System. Results: The LCA results show that the contribution of downstream processes is the most significant in all studied impact categories, since the relative contributions are: 89% in the GWP and AP categories and 77% in the POCP and EP categories, because of the demanded electricity during the lifetime of the machines, with values greater than 94% of the impact of downstream processes. The upstream processes present a moderate contribution in the POCP and EP categories, being their relative contribution major than 20% in both of them, because of cast iron (≈ 60% in POCP) and low-alloy steel (≈ 20% in POCP) materials which form part of the structural modules as well as pumps and motors (≈ 40% in EP). Discussion and Conclusions: The study takes a holistic view of the production and consumption of a milling machine range. The case study presents the adaptation of LCA methodology for a range of milling machines, in order to develop the EPD of these products. Simultaneously the LCA calculation of 28 machine reconfigurations is achieved through 9 modules, thus reducing time efforts and costs. The weakness of the representative check is located in the inventory analysis of the use stage. A future work could include a sensitivity analysis to evaluate more user conditions.