This research explores the relationship between demographic factors and road accident rates in England, UK, using census data and machine learning models. The study aims to address the challenge of gathering detailed individual driver behavior data by leveraging widely available demographic information. The theoretical framework is grounded in existing literature linking demographics to risky driving behaviors and the "close to home" effect, which suggests that 62% of accidents occur within 11 km of a driver's home. Using regression-based machine learning models, the study finds that census data can explain over 28% of the variance in road accident rates per capita. The results support the use of demographic data from national censuses for estimating road accident risks and demonstrate a methodology to explore potential indirect relationships between behaviors and road accident risk. The findings have implications for urban planning, policy-making, and emergency response strategies, emphasizing the importance of integrating demographic data into road safety models.This research explores the relationship between demographic factors and road accident rates in England, UK, using census data and machine learning models. The study aims to address the challenge of gathering detailed individual driver behavior data by leveraging widely available demographic information. The theoretical framework is grounded in existing literature linking demographics to risky driving behaviors and the "close to home" effect, which suggests that 62% of accidents occur within 11 km of a driver's home. Using regression-based machine learning models, the study finds that census data can explain over 28% of the variance in road accident rates per capita. The results support the use of demographic data from national censuses for estimating road accident risks and demonstrate a methodology to explore potential indirect relationships between behaviors and road accident risk. The findings have implications for urban planning, policy-making, and emergency response strategies, emphasizing the importance of integrating demographic data into road safety models.