This research focuses on the wear analysis of heavy vehicle gearbox systems, with particular emphasis on the case study of operational load fluctuations as a factor influencing wear rates. Heavy vehicles play a central role in various industries, and gearboxes are key components that affect operational performance and reliability. In this study, we collected operational data from various heavy vehicles operating under various conditions and environments. Through rigorous statistical analysis, we were able to identify a significant relationship between operational load fluctuations and gearbox wear rates. The results indicate that an increase in operational load fluctuations can proportionally increase the wear rate. These results have important implications in the development of smarter and more efficient maintenance strategies for heavy vehicles, which can reduce unexpected maintenance costs and increase gearbox service life. In addition, this study also confirmed that the basic assumptions in regression analysis, such as normality of residuals, homoscedasticity, and independence of residuals, were well met. This validates the results of the regression analysis and provides a solid basis for decision-making in the context of heavy vehicle maintenance. Recommendations for further research development include more detailed data collection, the use of more advanced analysis methods, and the application of sensor and IoT technologies for real-time monitoring. With continued research in this area, we can advance our understanding of wear on heavy vehicle gearboxes and support the development of smarter maintenance strategies in the heavy transportation industry.