Effective prediction of NOx and CO emissions from boilers is crucial for regulatory compliance and environmental protection. Key process parameters (KPIs) correlated with emission levels include combustion temperature, fuel composition, air-to-fuel ratio, and flue gas recirculation rates. By analyzing both historic and real-time data, it is possible to predict NOx and CO emissions accurately. This predictive capability allows for better operational adjustments, ensuring emissions remain within permissible limits while optimizing boiler performance. Advanced analytics and machine learning techniques enhance the precision of these predictions, contributing to more efficient and environmentally friendly boiler operations.