The Stock Prediction web application utilizes an LSTM (Long Short-Term Memory) model for forecasting stock prices. Python Flask serves as the backend framework, fetching historical stock data from Yahoo Finance. This data is processed and utilized to train the LSTM model, which then generates predictions for future stock prices.

Once the predictions are made, Flask converts the relevant information, including the stock data, predicted values, and any visualizations, into a JSON format. This JSON data is then sent to the frontend built with React.js.

In the frontend, React.js organizes and displays the received data in a user-friendly manner. Users can view the historical stock data, the predicted future values, and any accompanying visualizations, such as line graphs or candlestick charts. The interface is designed to be intuitive and visually appealing, providing users with valuable insights into the potential trends of the selected stock.