Machine learning is a type of artificial intelligence that generates predictions based on data by using past stock market indexes as training ground values. Machine learning makes use of a variety of models to make predictions more accurate and easier. The use of machine learning in stock market prediction technology is a trend that helps make better decisions while choosing assets to own. The aim of stock market prediction is to analyze trends and be able to predict the future value of an asset value over time. The analysis in this paper concentrates on asset value estimation utilizing LSTM-based machine learning. The results for the estimation of prices are conducted on assets like Gold, Bitcoin, and Apple Inc. stock. Open, close, low, and high data of assets, obtained from Yahoo Finance are taken into account while training the model. The proposed model can estimate the stock market's movement accurately for the next 30 days.