This session explores the use of no-code Machine Learning (ML) within AVEVA Unified Engineering to enable predictive workflows in engineering datasets without programming. Using historical schematic data from AVEVA Engineering, ML models trained through the Lexicon module can predict attributes for electrical and instrumentation datasheets, supporting faster data completion, improved consistency, and automated quality checks. The session demonstrates how engineering teams can apply ML directly within their data environment to move toward a more predictive and data-driven engineering process.