Preventive maintenance is essential for the safe and efficient operation of railway vehicles. This paper introduces a laser scanner system developed to measure critical wheel profile parameters, including the qR value (wheel profile conformity index), flange height (Sh), and flange thickness (Sd). These parameters are crucial for monitoring wheel wear and ensuring proper wheel-rail interaction. The laser scanning system provides real-time, high-precision measurements, enabling early detection of wear patterns that could lead to failures if left unaddressed. This non-contact, automated technology integrates seamlessly into existing maintenance workflows, reducing human error and enhancing decision-making capabilities. Maintenance teams can use the data to plan predictive interventions, reducing downtime, extending the life of both wheels and rails, and minimizing maintenance costs. The system has been tested in operational environments, demonstrating its effectiveness in improving the reliability and safety of railway vehicles. By offering a more efficient approach to wheel monitoring, this technology contributes to the future of predictive maintenance in the railway industry.