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This integration enhances car efficiency and addresses concerns about high fuel consumption and emissions in traditional vehicles. The transition to hybrid models reduces harmful petrol emissions, contributing positively to environmental sustainability and mitigating the impacts of global warming. Machine learning (ML) algorithms play a crucial role in optimizing and assessing the compatibility of typical automobiles with HEVs. Through rigorous testing and refinement, the proposed model exhibits improved accuracy, elevating performance from 81.76% to 86.68%. The incorporation of W\u2010Saw score and L\u2010Saw score metrics in an interdisciplinary research methodology further strengthens the optimized model\u2019s reliability and effectiveness. The model\u2019s robustness is evidenced by the high W\u2010Saw score of 8.8, indicating its strength, and a low L\u2010Saw Score of 3.3, highlighting minimal errors. 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