  The Tesla vehicles became very popular in the car industry as it was
affordable in the consumer market and it left no carbon footprint. Due to the
large decline in the stock prices of Tesla Inc. at the beginning of 2019, Tesla
owners started selling their vehicles in the used car market. These used car
prices depended on attributes such as the model of the vehicle, year of
production, miles driven, and the battery used for the vehicle. Prices were
different for a specific vehicle in different months. In this paper, it is
discussed how a machine learning technique is being implemented in order to
develop a second-hand Teslavehicle price prediction system. To reach this goal,
different machine learning techniques such as decision trees, support vector
machine (SVM), random forest, and deep learning were investigated and finally
was implemented with boosted decision tree regression. I the future, it is
intended to use a more sophisticated algorithm for better accuracy.
