Another powerful application of Machine Learning is predictive analytics in software development. By analyzing past project data, ML models can highlight modules most likely to fail, predict the severity of potential bugs, and recommend where additional testing is needed. This means quality assurance teams can prioritize their efforts more effectively, leading to fewer errors and smoother releases. Predictive models also improve cost estimation and resource planning. Instead of relying solely on human judgment.