A retrospective multivariate analysis of 37 clinical, biochemical, and hematological data was performed in 107 cases of primary myelodysplastic syndromes (MDS) in order to recognize their prognostic significance. The most important individual variables, isolated in a previous univariate analysis, were placed in a multiple regression modeling procedure to identify major significant prognostic factors. Multivariate analysis tends to identify prognostic variables containing significant independent predictive information. Characteristics were examined on both continuous and binary bases. The FAB classification was the first parameter entered in regression equations on both models, followed by platelet count, hemoglobin level, and circulating erythroblasts in the binary model, and by hemoglobin level, systemic symptoms, platelet count, age, and dyserythropoiesis in the continuous model. Our analysis confirms FAB classification as the main prognostic factor in MDS, supports the previously noted predictive value of platelet count, hemoglobin level, and age, and recognises the importance of circulating erythroblasts, systemic symptoms, and dyserythropoiesis as prognostic characteristics in MDS.