Neurons connect to each other through a myriad of dendritic and axonal arborisations. Dendritic structures provide the substrate for integration of postsynaptic potentials and control of action potential generation. Axonal structures provide the substrate for action potential dissemination and signalling to target neurons. The morphological complexity of dendritic arborisations is assumed to play a critical role in the transformation of spatio-temporal patterns of postsynaptic potentials into time-structured series of action potentials. Although these transformations lie at the basis of information processing in the brain, it is still far from understood how their details are influenced by dendritic shape. To facilitate research in this area, it is necessary that data on both the morphology and electrical properties of neurons, as well as computational tools for analysis, become available in an integrated way. This requires a combined effort from the fields of informatics and neurosciences (together called neuroinformatics) in order to create data acquisition, databasing and computational tools. Focusing on neuronal morphology, this chapter will give a brief review of the current neuroinformatics developments in both reconstruction techniques, morphological quantification, modeling of morphological complexity, modeling of function and the need for databasing neuronal morphologies. Additionally, one of the dendritic modeling approaches is described in more detail in the Appendix.