Periodontitis is a chronic inflammatory disease associated with the presence of dysbiotic microbial communities. Several studies interrogating periodontitis pathogenesis have utilized the murine ligature-induced periodontitis (LIP) model and have further examined the ligature-associated microbiome relying on 16S rRNA-based sequencing techniques. However, it is often very challenging to compare microbial profiles across studies due to important differences in bioinformatic processing and databases used for taxonomic assignment. Thus, our study aim was to reanalyze microbiome sequencing datasets from studies utilizing the LIP model through a standardized bioinformatic analysis pipeline, generating a comprehensive overview of microbial dysbiosis during experimental periodontitis.We conducted a reanalysis of 16S rDNA gene sequencing datasets from nine published studies utilizing the LIP model. Reads were grouped according to the hypervariable region of the 16S rDNA gene amplified (V1-V3 and V4), preprocessed, binned into operational taxonomic units and classified utilizing relevant databases. Alpha- and beta-diversity analyses were conducted, along with relative abundance profiling of microbial communities. Our findings revealed similar microbial richness and diversity across studies and determined shifts in microbial community structure determined by periodontitis induction and study of origin. Clear variations in the relative abundance of bacterial taxa were observed starting on day 5 after ligation and onward, consistent with a distinct microbial composition during health and experimental periodontitis. We also uncovered differentially represented bacterial taxa across studies, dominating periodontal health and LIP-associated communities. Collectively, this reanalysis provides a unified overview of microbial dysbiosis during the LIP model, providing new insights that aim to inform further studies dedicated to unraveling oral host–microbial interactions.