ABSTRACT This thesis examines and analyzes the use of data mining techniques and simulations as a forecasting tool. Decision making process for business can be risky. Corporate decision makers have to make decisions to protect company’s benefit and lower the risk. In order to evaluate data mining approach on forecasting, a tool, called IFF, was developed for evaluating and simulating forecasts. Specifically data mining techniques’ and simulation’s ability to predict, evaluate and validate Port Industry forecasts is tested. Accuracy is calculated with data mining methods. Finally the probability of user’s and simulation model’s confidentiality is calculated. The results of the research indicate that data mining approach on forecasting and Monte Carlo method have the capability to forecast on Port industry and, if properly analyzed, can give accurate results for forecasts.