Genome-wide studies are providing researchers with a potentially complete list of the molecular components present in living systems. It is now evident that several metal ions are essential to life and that metalloproteins, that is, proteins that require a metal ion to perform their physiological function, are widespread in all organisms. However, there is currently a lack of well-established experimental methods aimed at analyzing the complete set of metalloproteins encoded by an organism (the metalloproteome). This information is essential for a comprehensive understanding of the whole of the processes occurring in living systems. Predictive tools must thus be applied to define metalloproteomes. In this Account, we discuss the current progress in the development of bioinformatics methods for the prediction, based solely on protein sequences, of metalloproteins. With these methods, it is possible to scan entire proteomes for metalloproteins, such as zinc proteins or copper proteins, which are identified by the presence of specific metal-binding sites, metal-binding domains, or both. The predicted metalloproteins can be then analyzed to obtain information on their function and evolution. For example, the comparative analysis of the content and usage of different metalloproteins across living organisms can be used to obtain hints on the evolution of metalloproteomes. As case studies, we predicted the content of zinc, nonheme iron, and copper-proteins in a representative set of organisms taken from the three domains of life. The zinc proteome represents about 9% of the entire proteome in eukaryotes, but it ranges from 5% to 6% in prokaryotes, therefore indicating a substantial increase of the number of zinc proteins in higher organisms. In contrast, the number of nonheme iron proteins is relatively constant in eukaryotes and prokaryotes, and therefore their relative share diminishes in passing from archaea (about 7%), to bacteria (about 4%), to eukaryotes (about 1%). Copper proteins represent less than 1% of the proteomes in all the organisms studied. We also discuss the limits of these methods, the approaches used to overcome some of these limits to improve our predictions, and possible future developments in the field of bioinformatics-based investigation of metalloproteins. As a long-standing goal of the biological sciences, the understanding of life at the systems level, or systems biology, is experiencing a rekindling of interest; ready access to complete information on metalloproteomes is crucial to correctly represent the role of metal ions in living organisms.