Software quality and reliability is as important as delivering it within scheduled budget and time. Software quality models to identify high risk program modules are used. Identifying faults early in the software lifecycle can help to predict the need for quality checking, monitoring, and amount of testing required. Fault-proneness metric is used to calculate the chances of faults in the modules of the software. In software engineering fault proneness is a famous metric measurement of faults and failure. In the study of Neural Network (NN) the real-time defect data sets are taken from the online data repository.