The probability theory was considered as the most advanced and the best theory to deal with uncertainty (Cheeseman, 1985). This theory has emerged based on ideas of ambiguity and uncertainty. According to the probability theory, defining the probability of an event can be done by finding possible causal models where a given event occurs. In a mode of thinking, where connections between different aspects of the situation are known only in terms of probability, general information about observed events can be used to infer about the probability of other unobservable events. Hunter (1980) indicates that probabilities are unable to express important information about the direction of causal effect, information that might be crucial in some thinking situations.
Bhatnagar & Kanal (1992), argue that this kind of probabilistic reasoning is the closest rational causal thought. Whoever thinks this way, defines in any given situation the logical outcome.
While recognizing that the probability theory deals with drawing conclusions about probability – causality events, the appearance of the basic idea of analysis based on a limited data is very similar to Zadeh’s concept of data analysis according to the Fuzzy Logic model.