This study presents an extensive examination of emissions from passenger vehicles, particularly focusing on the benefits of hybrid vehicles over conventional vehicles powered by fossil fuels. Although hybrid vehicles have a more favorable environmental impact, their production is hindered by higher costs and production challenges. By utilizing a Linear Regression Model, this study confirms the positive correlation between fuel consumption and CO \(_2\) emissions, emphasizing that increased fuel consumption results in increased CO \(_2\) emissions. These findings highlight the need for policies that encourage the adoption and production of hybrid vehicles to mitigate vehicular pollution effectively. In addition, the study analyzed real-time vehicle emission data and employed predictive modeling to assess the influence of factors, including fuel type, driving habits, vehicle maintenance, and environmental conditions, on emissions. In addition, it compares laboratory-based emission tests with real-world measurements, revealing significant disparities and highlighting the importance of real-world emission monitoring. This study offers critical insights for policymaker and stakeholders working to develop sustainable transportation solution, and serves as a foundation for future strategies to address the environmental and health impacts of urban transportation. This study presents a linear regression model to predict vehicle CO \(_2\) emissions (g/km) from fuel consumption (L/100km) and vice versa, achieving 92.44% of accuracy for cars and 86.68% for vans. This tool facilitates comparisons of fuel consumption or CO \(_2\) emissions between cars and vans, helping policymakers and stakeholders craft sustainable transportation strategies.