The purpose of our proposed system is to predict the stock market from previous years stock data. Increase in uncertainty in stock market gives us the motive for our proposed system to make it easy and available for common people to know and avoid losses using other technologies available today. The approach consists of the following steps - Data pre-processing, clustering, classification and visualization. Classification and correlation of data set makes it easy to understand similarities & dissimilarities amongst the data objects. In our proposed system data collection was done from yfinance. The significance of our proposed system is to give the commoner an insight in stock market pattern and awareness to avoid losses in prior.