This chapter discusses the diagnosis of heart failure (HF) in terms of invasive/non-invasive and artificial intelligence/machine learning techniques. Non-invasive methods include physical therapy, taking blood pressure, and temperature measurement. The chapter explains diagnosis by invasive and non-invasive methods, and looks at what artificial intelligence is and presents fields and examples of artificial intelligence supported studies. Treatment in HF generally gives effective results, the purpose being a decrease in sudden death and an increase in survival time. Surgical methods and medical support devices are other method used in treatment. The chapter presents computer-aided diagnosis and decision support systems. It also explains machine learning, learning types, machine learning algorithms, and machine learning based diagnostic studies. One of the techniques that can be used to diagnose of HF is artificial intelligence and machine learning. One of the areas most supported by artificial intelligence is computer-aided decision making, thanks to its various capabilities, notably diagnosis and prediction.