<p>The intuitionistic fuzzy sets (IFS) were introduced as an extension to fuzzy sets to represent situations lacking confidence since fuzzy sets, on the one hand, only consider the positive side, while IFS, on the other, manage to include both negative and positive aspects, thus, making them more beneficial in numerous decision-making circumstances. Due to its ability to address vagueness and imprecision efficiently, it forms an important tool in reliability engineering as well. It is useful for risk assessment, maintenance plans and reliability analysis of several systems by addressing uncertainty appropriately. This review covers the developments in IFS, particularly in the field of reliability engineering, along with the application of its various extensions such as Pythagorean fuzzy sets, Fermatean fuzzy sets, generalized IFS, etc., to address different kinds of uncertain conditions. The theoretical basis of IFS and its real-world implementations highlight their adaptability in solving difficult problems. Hence, this work provides an overview of the advantages and applications of IFS in reliability analysis. The review emphasizes that more IFS-based tools are needed to make reliability engineering more reliable. It encourages further investigation and usage of IFS in various fields and decision support systems by highlighting current developments and future directions.</p>