Abstract- this research paper presents a comprehensive study on the prediction of used car prices using machine learning techniques in three distinct countries: India, Pakistan, and Germany. The rise of used cars sales is exponentially increasing. Car sellers sometimes take advantage of this scenario by listing unrealistic prices owing to the demand. Therefore, arises a need for a model that can assign a price for a vehicle by evaluating its features taking the prices of other cars into consideration. Using this knowledge base, accurate price prediction models can provide valuable insights to both buyers and sellers in these diverse automotive markets. Leveraging a variety of machine learning algorithms, this study aims to explore the challenges and opportunities associated with predicting used car prices across different economic and cultural contexts. The analysis considers a range of features, including car specifications, mileage, and year of manufacture, to develop models tailored to each country's market conditions.
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