Risk assessment is an important tool in decision-making process and it is highly important to accrue knowledge on the features of each and every existing data, information and model parameters involved in risk assessment process. It is observed that most frequently existing data/ information are construed in probabilistic conceptualization because it is an extremely well-built and well instituted Mathematical apparatus to treat uncertainty (aleatory) that arises due to inherent variability, natural stochasticity, environmental or structural variation across space or time, due to heterogeneity or the random character of natural processes. However, it is comprehensible that not each and every existing data, information and model parameters are influenced by this type of uncertainty and so it cannot be handled by conventional probability theory. However, model parameters may be fouled with uncertainty (epistemic) that arises due to lack of precision, deficiency in data, diminutive sample sizes or data acquisition from specialist opinion or subjective construal of existing data or information. In such situations, conventional probability theory is improper to characterize (epistemic) uncertainty. To overcome the drawback of probabilistic method, L.A Zadeh in 1965 commenced a new notion called fuzzy set theory.