Road transportation plays a vital role in the movement of people and goods, serving as a key driver of economic growth and national development. When properly managed, it contributes significantly to government revenue and individual livelihoods. However, if poorly managed, it can lead to serious negative consequences, including increased road accident fatalities. This study explores innovative approaches to reducing road accident deaths in southern Nigeria through statistical analysis and predictive modelling. The methodology used for this research includes 60 years classified (1960-2021) data collection from the Federal Road Safety Corps (FRSC) and the National Bureau of Statistics (NBS) of road transport accident cases, model development using regression techniques and analyzed using SPSS version 25.0, afterward, some proposed solutions for the observed causes of the road accident was established. From the result obtained, the data indicates that 2011 was the most severe year for road accidents in Nigeria, with the highest recorded number of casualties at 47,219, accounting for 41.8% of total cases. In contrast, 1961 had the lowest number of fatal cases at 193, making up only 1.21% of the total cases, highlighting a relatively lower impact on fatalities that year. The models demonstrate a high degree of fit, with correlation values reaching 97.2% for injured persons and 91.9% for people involved. The findings emphasize the importance of targeted interventions, such as stricter traffic law enforcement and infrastructure improvements, which are crucial for reducing road accidents in southern Nigeria. The strategic recommendations proposed in this study are essential for enhancing road safety and minimizing the socio-economic impacts of road accidents.