Predictive Diagnostics enables real-time condition monitoring and streamlined maintenance planning for vehicle fleets. It integrates a diagnostic unit, DDU display, predictive maintenance algorithms, and logistics information systems into a unified solution.

Using advanced machine learning, the system identifies anomalies, predicts component lifespans, and schedules preventive maintenance. This reduces unplanned downtime, extends asset lifespans, and lowers operational costs. The system continuously learns from new data, refining its predictions and improving accuracy over time to ensure optimal fleet performance and cost efficiency.

LPP has incorporated the diagnostic unit into armoured Czech Army vehicles such as the PANDUR II and T-72 through the VIBMS platform. LPP also collects and analyses data from the HORNET UGV to support predictive maintenance of unmanned ground vehicles.