In order to earn more money in less time in this pandemic period, the ultimate option is to invest some amount in the stock market. If we invest more then we will have more profit whenever we invest in a good company. In Stock exchange, the goal is to understand the future worth of the economic stock. The recent trend in stock market prediction innovations is making use of machine learning that makes forecasts based up on the worth’s of present stock exchange indices by training on their previous values. Our work analyzes machine learning algorithms and also say the best algorithms for predicting stock values. Also comparing results of four algorithms namely Linear Regression, LSTM, k –nearest neighbors, fb-prophet algorithms. Factors considered are open, close, high, date and last. Furthermore, the proposed work examines the use of the prediction system in real-world settings and also problems related to the precision of the overall worth are given, also provides a machine-learning model to forecast the long life of stock in a open market. The effective forecast of the stock will certainly be a excellent possession for stock exchange organizations as well as will certainly provide real-life solutions stock capitalists encounter.