Acinetobacter baumannii is an important nosocomial pathogen that often affects critically ill patients in intensive care units. β-Lactam antibiotics are the most commonly prescribed drugs for infectious diseases caused by A. baumannii. Our aim is to develop an accurate and rapid shotgun proteomics method for the identification of β-lactam-resistant A. baumannii pathogens. In the present study, we used automated data-dependent scanning on a nano-LC/ion trap mass spectrometer to characterize proteotypic peptides of A. baumannii. Then, we used SEQUEST software to search specific databases, the β-lactam-resistance protein database of A. baumannii (BRPDAB). We successfully found a number of associated antibiotic-resistant proteins, including AmpC, β-lactamase, and carO, in clinical resistant strains of A. baumannii and differentiated them from wild-type A. baumannii strains. We used the results of the search to identify A. baumannii pathogens and found a β-lactam-resistant clinical strain of A. baumannii using Uniprot annotations, Gene Ontology (GO), and BLAST bioinformatics tools. This proteomic study will provide a platform for the rapid diagnosis of wild-type and resistant strains of A. baumannii, which would be useful for the medical treatment of these strains.