Defect prediction helps in analysing the flaws and errors in software. This field is widely under research in recent days because of the prevalence of errors due to carelessness in design and coding. Recent research on call graph model based software defect prediction shows the correlation between the call graph based metrics and bugs. In this research,call graph based ranking (CGBR) along with the size and complexity metrics is used to measure the quality of the software. This CGBR algorithm prioritizes the functional sub-systems which apply to the software defect prediction models. Size and Complexity metrics evaluate the quality of the software which measures the complexity of individual module. Finally, a comparison of three classifier algorithms is made and the best one is selected to predict the defective status of the software modules. © Research India Publications.