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The objective of this research is to apply the various machine learning approaches, such as Case-Based Reasoning and Fuzzy logic, to predict software quality. The system predicts the error after accepting the values of certain parameters of the software. This paper advocates the use of case-based reasoning (i.e., CBR) to build a software quality prediction system with the help of human experts. The prediction is based on analogy. We have used different similarity measures to find the best method that increases reliability. This software is compiled using Turbo C++ 3.0 and hence it is very compact and standalone. 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