Background Fuzzy soft sets are well-established for decision-making under uncertainty. However, integrating soft set theory with fuzzy codes remains unexplored, as fuzzy soft code sets have not addressed these concepts. This study presents novel fuzzy soft codes and discusses their application in diagnosing medical conditions and decision-making, bridging a critical gap in the literature. Methods Numerous scholars have examined fuzzy sets, fuzzy codes, and the theory of fuzzy soft sets and their applications over the years. This paper introduces the novel concept of fuzzy soft codes by combining fuzzy soft set theory with the notion of fuzzy codes, inspired by Ozkan’s 2002 definition of fuzzy codes. Results We define fuzzy soft codes as a parameterized family of fuzzy codes, detailing their matrix representation, set-theoretic operations, and algebraic properties. A new decision-making method using choice and score values from comparison tables is introduced. An example demonstrates its effectiveness for selecting optimal objects, proving its real-world potential in areas like medical diagnosis. This bridges a key theoretical gap and enables future extensions like intuitionistic fuzzy soft codes. Conclusions This study addresses a gap in the integration of soft set theory with the notion of fuzzy codes. The primary objective is to introduce the concept of fuzzy soft codes within the context of decision-making by merging fundamental ideas from soft set theory and fuzzy coding, while also examining several of their key properties. Additionally, a practical example is provided to demonstrate how this approach can be effectively utilized across a range of real world problem.
Woldie et al. (2025) studied this question.