Heart failure (HF) is a global pandemic currently affecting up to 16 million people in Europe. In Serbia it is also major cause of death and disability. It is a complex clinical syndrome associated with impaired heart function, poor quality of life for patients and high healthcare costs. We propose to address this disease with an computational modeling and AI-based Decision Support System for HF. In this project, we will develop the DSS, which integrates the high-quality health-relevant data from existing databases in hospitals, and AI-driven algorithms and analytics. Our work plan, therefore, comprises a retrospective and prospective clinical studies to collect patient-specific data using state-of-the-art existing and novel technologies and conduct proof-of-concept and clinical validation studies. Applying data mining approach, bioinformatics, and artificial intelligence on data collected, it further develops a Patient-specific digital library, AI algorithms and analytical tools for risk stratification, early diagnosis, and progression prediction in HF. The algorithms and analytical tools will be integrated into the computerised, AI-based DSS, which will be tailored to accommodate primary and secondary care clinical needs. Pilot implementation of the DSS across clinical centres in Serbia and Europe will be conducted. AI and computational modelling can be very powerful tool for diagnostic and risk stratification of patient with heart failure.