In recent years, the issue of credit risk has been given increasingly more attention. This is because, as research shows, many of the bank failures observed had resulted from the poor condition of their loan portfolios. The quality of every loan can be expressed by the rating ascribed to it. Ratings classify borrowers into categories by the degree of bankruptcy risk. The quality of the loan portfolio can be measured with the distribution of its ratings. The more low-rating credits, the worse the portfolio. This quality may change with time, following the shifts (migration) within the portfolio. Certain loans win higher rating, others slip, still others remain unchanged. Therefore methods allowing to forecast future rating distributions are of great practical value. When the trends in a portfolio´s development and, consequently, its future quality are known, it is possible to identify the threats and act in order to prevent them. Simple mathematical instruments, such as finite Markov chains, are utilized to forecast the future ratings distribution of a portfolio. Based on the evolution of the portfolio in the past, they stake out its future development. These methods are presented in the paper with a modification by the author allowing for an inclusion of new credits in the portfolio.