Software quality can be predicted before deployment using a new approach that combines expertise from existing models. By using a genetic algorithm to create a "composite" model, accuracy in predicting module fault-proneness within software development environments is improved. This method works well for different software development circumstances, making it more reliable than traditional prediction models. Learning from existing software models helps overcome generalizability issues and lack of data in software engineering.