ABSTRACTDecades of ongoing research has established that oral microbial communities play a role in oral diseases such as periodontitis and caries. Yet the detection of oral bacteria and the profiling of oral polymicrobial communities currently rely on methods that are costly, slow, and technically complex, such as qPCR or next-generation sequencing. For the widescale screening of oral microorganisms suitable for point-of-care settings, there exists the need for a low-cost, rapid detection technique. Here, we tailored the novel CRISPR-Cas-based assay SHERLOCK for the species-specific detection of oral bacteria. We developed a computational pipeline capable of generating constructs suitable for SHERLOCK and experimentally validated the detection of seven oral bacteria. We achieved detection within the single-molecule range that remained specific in the presence of off-target DNA found within saliva. Further, we adapted the assay for detecting target sequences directly from unprocessed saliva samples. The results of our detection, when tested on 30 healthy human saliva samples, fully aligned with 16S rRNA sequencing. Looking forward, this method of detecting oral bacteria is highly scalable and can be easily optimized for implementation at point-of-care settings.