The human pathogen Streptococcus pyogenes (Group A Streptococcus or GAS) are a versatile Gram-positive cocci that havw shown complex modes of regulation of its different virulence factors. Discoveries of a few small non-coding RNAs (sRNAs) in S. pyogenes and their influence on the expression of virulence factors revealed an important role of sRNAs on S. pyogenes virulence. The genome-wide analysis of bacterial genomes for the discovery of sRNAs through computational methods has become an effective way to discover new sRNAs. In this study we provided a computational scheme where three different algorithms (RNAz, eQRNA, and sRNAPredict) were combined to increase the probabilities of predicting putative sRNAs within S. pyogenes' intergenic regions (IGR). A total of 46 candidates were chosen based on our criteria, and through Northern blot we analyzed each candidate. We obtained hybridization signals from twelve newly discovered sRNAs in S. pyogenes. Subsequently, we analyzed their sequence and their location within the IGR to find a putative -10 promoter region and possible Rho-independent terminator site, and their possible targets through computational methods. We further expanded our analysis of the new sRNAs by using Real-Time RT-PCR to determine the expression of sRNAs during different phases of growth. Our results showed that our computational scheme and experimental method was effective in predicting sRNAs previously undiscovered in S. pyogenes, and that more sRNAs are yet to be discovered and characterized, helping to further understand the regulation of virulence factors in S. pyogenes