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Objectives We built and validated a new heart failure (HF) prognostic model which integrates cardiopulmonary exercise test (CPET) parameters with easy-to-obtain clinical, laboratory, and echocardiographic variables. Background HF prognostication is a challenging medical judgment, constrained by a magnitude of uncertainty. Methods Our risk model was derived from a cohort of 2716 systolic HF patients followed in 13 Italian centers. Median follow up was 1041days (range 4–5185). Cox proportional hazard regression analysis with stepwise selection of variables was used, followed by cross-validation procedure. The study end-point was a composite of cardiovascular death and urgent heart transplant. Results Six variables (hemoglobin, Na + , kidney function by means of MDRD, left ventricle ejection fraction [echocardiography], peak oxygen consumption [% pred] and VE/VCO 2 slope) out of the several evaluated resulted independently related to prognosis. A score was built from Metabolic Exercise Cardiac Kidney Indexes, the MECKI score, which identified the risk of study end-point with AUC values of 0.804 (0.754–0.852) at 1year, 0.789 (0.750–0.828) at 2years, 0.762 (0.726–0.799) at 3years and 0.760 (0.724–0.796) at 4years. Conclusions This is the first large-scale multicenter study where a prognostic score, the MECKI score, has been built for systolic HF patients considering CPET data combined with clinical, laboratory and echocardiographic measurements. In the present population, the MECKI score has been successfully validated, performing very high AUC.