The fuzzy logic represents the relationship between precision and uncertainty. As the uncertainty in a theme is high, then less precise we can be in our conception. A binary logic admits only the opposites of true and false, a logic which does not admit digress of truth and there are no variations in magnitudes, but only two possible results. As more complex a system is, then more imprecise or inexact is the information that we have to the system. Aristotle mentioned that “It is the mark of an instructed mind to rest satisfied with that degree of precision which the nature of the subject admits, and not to seek exactness where only an approximation of the truth is possible”. So, Aristotelian logic does not admit imprecision in truth. However, Aristotle’s quote is so relevant with the approach that admits uncertainty. The theme is the balance between the precision with the uncertainty in a concept. The case of imprecision comes up from physical processes upon on imprecise human reasoning. Requiring precision in engineering models and economics means high cost and long lead times in production and development. So, considering the use of fuzzy logic then ponder the need for exploiting the tolerance for imprecision. According to the traditional view of science, uncertainty represents an undesirable situation, and must be excluded at any cost. Max Black referred to vagueness, where the possible states are not clearly. According to his essay in 1937 known as “Vagueness: An exercise in logical analysis” presented some remarks by Plato about Uncertainty in geometry. Bertand Russell in 1923 pointed out that “all traditional logic habitually assumes that precise symbols are being employed”. So, follow some proposals.