Introduction: Tuberculosis (TB), commonly caused by Mycobacterium tuberculosis (Mtb), is one of the ten leading causes of death worldwide. The gold standard, microbiological culture for detection and differentiation of mycobac-teria are time-consuming and laborious. The use of fast, easy and sensitive nucleic acid amplification tests (NAATs) for diagnosis of TB remains challenging because there is a high degree of homology within Mtb complex (MTBC) members and absence of target genes in the genome of some strains. This study aimed to identify new candidate genetic marker and to design specific primers to detect Mtb using in silico methods. Methods: Using Basic Local Alignment Search Tool (BLAST) program, Mtb H37Rv chromosome reference genome sequence was mapped with other MTBC members and a single nucleotide polymorphism (SNP) at Rv1970 was found to be specific only for Mtb strains. Mismatch amplification mutation assay (MAMA) combine with polymerase chain reaction (PCR) was used as an alternative method to detect the point mutation. MAMA primers targeting the SNP were designed using Primer-BLAST and the PCR assay was optimized via Taguchi method. Results: The assay amplified a 112 bp gene fragment and was able to detect all Mtb strains, but not the other MTBC members and non-tuberculous Mycobacte-ria. The detection limit of the assay was 60 pg/μl. Conclusion: Bioinformatics has provided predictive identification of many new target markers. The designed primers were found to be highly specific at single-gene target resolution for detection of Mtb.