Recurrent Neural Networks (RNN), particularly Long Short Term Memory (LSTM) models, are widely regarded as effective tools for predicting stock market movements. By examining past data and analyzing market patterns, these models can forecast future stock prices with a high level of accuracy. In addition to RNNs, machine learning methods such as Random Forest and Support Vector Machines (SVM) are commonly used in financial prediction processes.