Researchers have linked Chlamydia pneumoniae (C. pneumoniae), a type of bacteria that cannot survive outside of cells and is resistant to gram staining, to many autoimmune diseases. People hypothesized that C. pneumoniae had a harmful function due to its tendency to inhabit human endothelium and epithelial tissue. This study implemented multiple bioinformatics tools and databases to understand the possible function of the CT670 hypothetical protein of C. pneumoniae. The physicochemical parameters showed the protein's half-life in different media. These parameters also displayed the protein's theoretical isoelectric point, aliphatic index, GRAVY value, extinction coefficient, instability index, as well as the amino acids and atoms that comprise it. Amino acid composition measured the percentage of amino acids present in the selected protein, with glutamate demonstrated as the greatest proportion. Moreover, hydrogen was the most abundant ratio in terms of the atomic composition of the protein, followed by carbon, oxygen, nitrogen, and sulfur. The PPI networks reveal its potential primary and secondary interactions with other proteins. We modeled and assessed the secondary and tertiary structures to understand the nature of the selected protein. Computational functional analysis predicted that the protein would be a chaperone effector. By designing and developing drugs and vaccines, we can use this protein as a target for further analysis to combat diseases caused by C. pneumoniae.