This presentation outlines how real-time predictive analysis is transforming Formula 1 racing, moving beyond traditional engineering applications to inform immediate strategic and operational decisions. It highlights the massive volume of data generated by modern F1 cars and the challenges of processing and transmitting this data instantly to inform split-second choices regarding strategy, performance, risk management, and competitor reactions. The text details various data sources and machine learning applications used to build predictive models for areas like tire degradation, weather patterns, fuel efficiency, and driver and competitor behavior, ultimately aiming for a "millisecond advantage" in competition. Finally, it touches on the technical, implementation, and ethical considerations, including edge computing and the integration of AI with human decision-making, while also exploring the potential impact of this technology beyond motorsport.