Bitcoin is a highly volatile and widely traded crypto-currency. This work uses LSTM (Long Short Term Memory), a deep learning model inorder to predict the price of bitcoin and the real time crypto-currency trading data extracted from CCXT (Crypto-currency Exchange Trading library). LSTM is a type of recurrent neural network (RNN) that is good for real-time data analysis due to its ability to capture long-term dependencies and patterns. The CCXT library provides instant access to market data from multiple crypto-currency exchanges, allowing models to learn new information. The study exposes the potential of the combination of LSTM with real-time data for real-time financial predictions. In this work we aim to predict the bitcoin’s price with highest possible accuracy based on the number of days given by the user.