Abstarct: Aabstract In this thesis, the Hull-White model is applied to predict the price of Sekeh Emami using daily data from 1395/01/05 to 1402/12/07 and the maximum likelihood estimation method. The main objective of the research is to estimate the parameters of the Hull-White model and evaluate the accuracy and effectiveness of this model in predicting the volatility and price trends of Sekeh Emami. Initially, the price data of Sekeh Emami was collected and processed from reliable sources. Then, the Hull-White model was simulated using statistical methods and the R software, and the key parameters of the model, including the mean reversion rate (α), volatility (σ), and long-term mean rate (θ), were estimated. The simulation results and statistical analyses indicated that the Hull-White model effectively models the volatility and price behavior of Sekeh Emami. In the final section, suggestions for improving the model and future research are provided, including sensitivity analysis of parameters, comparison with other models, adding important economic variables, and utilizing machine learning techniques. The results of this study show that the Hull-White model can be used as an effective tool in predicting the price of Sekeh Emami and managing risk in financial markets.