Current trends in medical management of advanced heart failure and transplant medicine and the enactment of a detailed national transplant laws forced a change towards allocation driven by disease severity. The aim of this study was (i) to examine whether the current UNOS status 1a/1b/2 classification could be improved, (ii) create a new model which allows the calculation of a continuous index based of a few easily obtained variables. The available clinical profile data were first classified into physiological subscores: (1) urgency score based on patient’s residency, administration of IV cathecholamines, VAD implant, requirement of hemodialysis and or hemofiltration, (2) left ventricular heart failure score, based on cardiac index and LVEF, (3) right ventricular heart failure score based on PAM, TPG, PVR, ZVD, (4) systemic heart failure score based on sodium, heart rate, creatinine, peak VO2 and MAP and the factors patient’s age, AB0 and body surface. All patients registered in Germany in 1997 [N=889] were used as derivation set, the total German 1998 cohort [N=897] was used as validation set. Only the urgency score and the left ventricular heart failure score were found to be significantly associated with mortality and retained in the model, a summarizing index called German Transplant Society score (GTS) was then calculated. The GTS score enabled a discrimination between high, medium and low risk patients. Results from a Cox PH model showed that the addition of the GTS score significantly improved a prediction model based on the UNOS classess (p=0.037). The use of this continuous disease severity index based on 7 objective variables would allow a perfect patient’s ranking, thereby enabling an urgency driven allocation without the necessity to downweigh it by waiting time.