This work focuses on finding and rationalizing the building principles of clusters with approximately 300 atoms of different types of metals: main group elements (Al, Sn), alkaline earth metals (Mg), transition metals (Pd) and clusters consisting of two different elements (Ir and Pt). Two tools are inevitable for this purpose: (i) quantum chemical methods that are able to treat a given cluster with both sufficient accuracy and efficiency and (ii) algorithms that are able to systematically scan the (3n−6)-dimensional potential surface of an n-atomic cluster for promising isomers. Currently, the only quantum chemical method that can be applied to metal clusters is density functional theory (DFT). Other methods either do not account for the multi-reference character of metal clusters or are too expensive and thus can be applied only to clusters of very few atoms, which usually is not sufficient for studying the building principles. The accuracy of DFT is not known a priori, but extrapolations to bulk values from calculated series of data show satisfying agreement with experimental data. For scans of the potential surface, simulated annealing techniques or genetic algorithms were used for the smaller clusters (approx. 20-30 atoms), and for the larger clusters considerations were restricted to selected packings and shapes. For the mixed-metallic clusters, perturbation theory turned out to be efficient and successful for finding the most promising distributions of the two atom types at the different sites.