Lithium-ion batteries play a major role in a large number of applications ranging from portable devices to electric vehicles. In recent years, lithium-ion batteries became more and more important due to their preferable electrochemical properties as for example a relatively high energy density. As it has been shown for instance in , the morphology of the electrodes mainly influences the overall battery performance. Therefore, a deeper understanding of the microstructure of cathodes as well as anodes is an important task with regard to the optimization of functionality. Consequently, the investigation of the manufacturing process of the electrodes and its influence on their microstrucuture is an essential part of battery research [2,3]. The cathode manufacturing process is of special interest since it mainly influences the overall performance, see . We will focus on eight experimentally manufactured cathodes described in . The full 3D information of these differently compacted cathodes with porosities ranging from 18 to 50 % has been obtained using synchrotron tomography, which allows us to take spatially localized features into account. With the aid of several image processing techniques we are able to obtain phase- as well as particle-segmented image data, which provide valuable information regarding the electrochemical performance. In addition, the microstructural analysis using 3D image data allows the investigation of characteristics which can not be determined experimentally. Furthermore, the combination of parametric probability distributions and least-squares regression is a powerful tool in order to predict the distributions of microstructural characteristics as a function of the compaction load. In our future research, this approach will be further extended by using a parametric stochastic 3D microstructure model, which will be fitted to the considered cathodes. Several stochastic microstructure models for electrodes in lithium-ion batteries have been developed in ,  and . This allows us to describe the 3D morphology of the cathode using only a few parameters. By least-squares regression analysis, we are finally able to predict the microstructure of cathodes for an arbitrary compaction load, which can be used to provide a wide spectrum of virtual but realistic 3D microstructures as valuable input for numerical simulations.