Machine learning is applied in predictive maintenance by analyzing data from sensors and equipment to forecast potential failures before they occur. By employing algorithms that learn from historical data, organizations can identify patterns and anomalies that indicate the need for maintenance. This proactive approach minimizes downtime and reduces operational costs while enhancing overall equipment reliability. Predictive maintenance ensures that assets are serviced when necessary, optimizing resource allocation and extending the lifespan of critical machinery.