Machine learning models often encounter challenges post-deployment, such as discrepancies between training and production data, necessitating effective monitoring to ensure optimal performance. Comet MPM (Model Production Monitoring) addresses this need by providing real-time insights into model performance, allowing data scientists to detect issues like accuracy drift and other discrepancies that arise when production data diverges from expectations. This tool helps bridge the gap between the training and production phases of the ML lifecycle, ensuring that models continue to meet business KPIs and adapt to evolving environmental data conditions. By enhancing visibility into model performance after deployment, Comet MPM aids in maintaining model effectiveness and mitigating the risks of outdated or misaligned models, which can be costly and negatively impact business outcomes.