ABSTRACT
As the Indian auto-industry entered BS-VI era from April 2020, the value proposition of used cars grew stronger, as the new cars became expensive due to additional technology costs. Moreover, the unavailability of public transport and fear of infection force people toward self-mobility during the outbreak of Covid-19 pandemic. But, the surge in demand for used cars made some car sellers to take advantage from customers by listing higher prices than normal. In order to help consumers aware of market trends and prices for used cars, there comes the need to create a model that can predict the cost of used cars by taking into consideration about different features and prices of other cars present in the country. In this paper, we have used different machine learning algorithms such as k-nearest neighbor (KNN), random forest regression, decision tree, and light gradient boosting machine (LightGBM) which is able to predict the price of used cars based on different features specific to Indian buyers, and we have implemented the best model by comparing with other models to serve our cause. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.