This project is concerned with predicting the price of Bitcoin using supervised machine learning approach. The goal is to ascertain with what accuracy can the direction of Bitcoin price in USD can be predicted. The task is achieved with varying degrees of success through the implementation of a Bayesian Regression.The popular ARIMA model for time series forecasting is implemented as a comparison to Holt’s Forecasting Model, exponential triple smoothing and Bayesian Regression. It can clearly be seen that Bayesian regression gives the best forecasting model for bitcoin price prediction. It has a very low Mean accuracy prediction error of 7.82 which is way lower compared to other models.The model is run only for 10 iterations or Markov chains and increasing this number would further improve the model accuracy.The implementation is done in R.