Battery State-of-Health modelling can significantly reduce the amount of costly laboratory tests in the application being analyzed. This paper discusses the prediction of the State-of-Health, an indicator of battery life, using support vector regression. This experiment is performed on a sample cell of a lithium-ion battery, which is subjected to a method known as the Constant Current Constant Voltage method, where the battery is charged and discharged at a constant current of 0.5 C. Although this method in this paper is applied in laboratory conditions and it is a controlled method, or it deviates from the battery cycling of real applications, it can be used in these applications, thus the scope of this research can predict the State-of-Health also in the areas of batteries used in mobile devices or electromobility. The State-of-Health indicator then determines whether the battery is still suitable for that primary application. Assuming that we can predict this parameter with some accuracy, it is then also possible to tell after what length of time a battery will need to be replaced and when it will be suitable for secondary applications such as stationary storage. Once it reaches that state, this calculation can be further applied to those applications as well.