The topic of global warming is and will continue to be a crucial topic of this millennium. Freight transport, as a producer of greenhouse gas (hereinafter GHG) emissions, makes a significant contribution to the greenhouse effect. Large supply chains and large volumes of freight transport, which imply the production of significant volumes of GHG emissions, characterize the automotive industry (hereinafter AI). Thanks to these premises, it is necessary to seek and develop tools for reducing the volume of GHG emissions produced from the logistic activities of the AI, while maintaining the required level of logistic services. The assumptions for the calculation of GHG emissions from railway freight transport (hereinafter RFT) in the AI were identified through the use of semi-structured interviewing. Available railway freight GHG emission calculators were identified and analyzed from the perspective of suitability for the AI using a comparative content analysis. The main result of this manuscript is the proposal of a fully customized approach to GHG emission calculations in RFT for the AI. This approach was proposed, applied, and verified in the form of an interpretative case study. The use of this approach can be expected in support of logistic planning and decision making.