The Vietnamese stock market, established in 2000, has rapidly developed to become an integral part of the national economy. With a growing population of over 100 million, in which more than 8% are currently participating in the stock market, there is a urgent need for an advanced recommendation system to help investors navigate the complexities of this dynamic environment. To address these challenges, we have developed a stock market recommendation system utilizing advanced financial indicators and machine learning algorithms. The system analyzes a comprehensive dataset, including stock prices, financial reports, and news articles, to identify investment opportunities and manage risks. Our analysis shows that financial indicators identify well-performing stocks. The K-means algorithm effectively classifies stocks based on growth and price volatility, Multiple Linear Regression helps assess seasonality, trends, and the impact of news on stock prices, and technical indicators provide real-time trading signals, helping investors save time on information retrieval, minimize investment risks, identify opportunities, and make effective investment decisions. Our system supports informed decision-making, promoting market transparency and stability. Future work will focus on integrating stock price prediction models and refining sentiment analysis techniques to enhance the system’s accuracy and relevance further.