Aims: Some Geobacillus species have highly similar 16S rRNA gene sequences, making 16S rDNA sequence analysis-based identification problematic. To overcome this limitation, recA and rpoB sequence analysis was evaluated as an alternative for distinguishing Geobacillus species. Methods and Results: The phylogram of 16S rRNA gene sequences inferred from the neighbour-joining method showed that nine clusters of Geobacillus species were characterized with bootstrap values >90%. The recA and rpoB sequences of 10 reference strains in clusters V, VIb and VIc were amplified and sequenced using consensus primers. Alignment of recA sequences in clusters V, VIb and VIc revealed three types of recA genes, consistent with the putative amino acid sequences and in vivo recA splicing analysis. The phylogram constructed from rpoB sequences showed more divergence than that constructed from 16S rRNA gene sequences. Conclusions: recA and rpoB sequence analysis differentiated closely-related Geobacillus species and provided direct evidence for reclassifying some species dubiously categorized as Geobacilli. Additionally, this study revealed three types of recA genes in the different Geobacillus species. Significance and Impact of the Study: This study highlights the advantage of recA and rpoB sequence analysis to supplement 16S rRNA gene sequence analysis for efficient and convenient determination of Geobacillus species.