Battery production has become an increasingly important issue for industry e.g. due to the advent of electric cars and the greening of grids. The battery production chain is very interdisciplinary and consists of many specialised, innovative processes and numerous influencing factors. In contrast to more established sectors, processes and their interactions are not well understood yet. Thus, this paper presents a data mining approach for predicting different quality parameters of battery cells based on extensive data acquisition over the whole process chain. The results can be used to improve the planning and control of battery production.