The locations of many manufacturing companies are distributed globally. This has led to the developmentof historically grown global production networks whose structure is often very complex, not transparent andinfluenced by many factors. The high number, as well as the volatility of the influencing factors anddependencies in the network additionally, complicate the network configuration. As a result, adaptationneeds and optimization possibilities are recognized too late or not at all. In order to enable early recognitionof saving potentials, active monitoring and analysis of changes and dependencies of the influencing factorson the production network is needed. The necessary consideration of a multitude of influencing factorsrequires further tools to be manageable by the network planner. Therefore, databased methods can be usedas support for the forecast and the determination of dependencies of influencing factors. In other researchfields, regression analysis is an established method for a databased analysis. This paper focuses on the useof regression analysis in global production networks. It is essential for an accurate analysis, to choose theright regression method out of the many different types in existence. A systematic literature review isconducted to establish an overview of regression methods used in other research fields. A search strategy isdeveloped and implemented and the key findings of the literature review are derived and evaluated. In thesecond step, a new approach for the pre-selection of suitable regression methods for the determination ofinteractions and forecasts in global production networks is proposed.