One of the most important issues in the world economy is the use of stagnant capital for the economic development of any country, and this requires a strategic policy to attract domestic and foreign investors. The general purpose is to investigate the adaptability of Iranian stock market behavior with other foreign financial markets according to Elliott wave theory model of technical analysis tools and classification algorithms. Therefore, the price movement trend in the total index and the total weighted index of the Iranian Stock Exchange as a thermometer of the economy and an indicator of the general situation of the Iranian stock market has been studied. First, the variables of Elliott Wave Oscillation and Relative strength index and Close changes, daily for the total index from 14/05/2008 to 25/11/2020 and the total weighted index from 04/05/2015 to 01/12/2020 calculated and accordingly, the movement trend was labeled into buying, selling and maintaining. Then, classification algorithms such as decision tree, K nearest neighbor, linear support vector machine were used to predict future trends. The results showed that the accuracy of Decision tree and the K nearest neighbor algorithms in predicting labels was above 90%. Therefore, the use of technical methods and proposed algorithms can help investors in determining the future trend of the total index and the total weighted index.