Reshoring decisions are associated with both high complexity and uncertainty. The increased complexity is due to the vast number of factors that need to be considered, while the uncertainty is due to the lack of sufficient information. The existing decision-making frameworks are few and theoretical and have not incorporated uncertainty and complexity aspects. Moreover, they do not provide automatic or digital decision support. In order to deal with this, one of the essential branches of mathematics called fuzzy logic is integrated together with traditional analytical hierarchy process (AHP). The aim of this study is to investigate the feasibility of fuzzy analytical hierarchy process (FAHP) as a tool for reshoring decision making when complexity and uncertainty are involved. In order to achieve this, the FAHP was applied to six reshoring criteria, which also correspond to competitive priorities. The findings show that the criterion Quality received the highest weight, followed by the criterion Cost. It was found that the criterion Sustainability resulted in zero priority weight, which means that this criterion was not given importance in this decision. This reduced the complexity of the decision by removing irrelevant criteria in decision making. The fuzzy sets used for pairwise comparisons also incorporated uncertainty in the decision. The FAHP is a feasible tool for reshoring decision making for most of the decision scenarios. This reshoring decision-making tool is automatic, simple and less time consuming, and can be adapted to suit unique reshoring cases.