This chapter covers various aspects of uncertainty and their connection to fuzzy logic. Uncertainty is the main reason why humans are free to choose. Researchers are still struggling to create a common understanding of uncertainty. There are some theories you can follow to make decisions in uncertain situations. The concept of fuzzy sets and their extensions has been understood in various ways in the literature. Discussions of uncertainty are often encountered in, but not limited to, the following areas: decision science, artificial intelligence, legal facts, economics, medicine, organizational open systems theory, psychology, and physics. Many actions and strategies are designed to deal with or reduce uncertainty to make life easier for decision makers, but there are no generally accepted theories in academia. Measurement errors can lead to fake results, such as wrong results due to human errors and instrument malfunction. Real numbers and other spurious errors are not taken into account in the statistical evaluation of measurement uncertainty. Fuzzy sets expand the concept of sets, so they can account for epistemological uncertainties. Graduality, epistemological uncertainty, and ambiguity appear to interact closely with each other within fuzzy set theory.