Predictive maintenance leverages computer vision, data science, and predictive analytics to optimize equipment maintenance by predicting when components need repairs before failures occur. This technology is especially beneficial for critical infrastructure such as aircraft, turbines, and pipelines, where failures can incur high costs and safety risks. By utilizing AI models, predictive maintenance can improve equipment lifespan, reduce downtime, and manage repair costs effectively. For instance, Clarifai's visual predictive maintenance (vPMx) system uses high-resolution imagery and AI to detect defects in aircraft components, providing accurate, time-series data for maintenance prioritization. This approach not only enhances safety by reducing manual inspection errors but also prevents catastrophic failures and reduces maintenance costs. The application of vPMx extends beyond aviation to sectors like buildings, vehicles, power lines, and transportation infrastructure, demonstrating its versatility in maintaining various types of equipment and infrastructure.