The purpose of this dissertation is the presentation of the forecasting freight rates with well-known methods Markov Chain which uses time series from Clarckson’s, with two routes and applications in the statistical package, R. The need to forecast charter revenue for shipping companies is examined. The concept of bulk shipping and the importance of ship sizes are introduced. Various freight rates forecasting methods are mentioned such as ARMA, with an emphasis on the Markov Chain Method. The statistical analysis of data for two shipping routes to understand the tendance of both time series. The freight rates forecasting using three-dimensional transition matrices and the apply in Markov Chain Model, is studied. Also, limitations of the research are mentioned, such as the uncertainty in determining the demand and geopolitical factors. The thesis concludes with ideas for future development, including reducing uncertainty in forecasts and evolving the Markov model into a Hidden Markov Model (HMM) for more detailed forecasting.