Several useful models have been developed by the software engineering community to elucidate the periodic growth of life cycle and calculate the effort of cost estimation in a precise manner. One of the commonly used machines learning technique is the analogy method that cannot handle the categorical variables efficiently. In general project attributes of cost estimation are often measured in terms of linguistic values. These imprecise values leads to analogous while explaining the process. The proposed method is an integrated approach of combining analogy with the fuzzy, based on reasoning by analogy for handling both numerical and categorical variables where the uncertainty and imprecision solution is also identified by the behavior of linguistic values utilized in the software projects.