Background: Clostridium botulinum and related clostridia express extremely potent toxins known as botulinum neurotoxins (BoNTs) that cause severe, potentially lethal intoxications in humans. These BoNT-producing bacteria are categorized in seven major toxinotypes (A through G) and several subtypes. The high diversity in nucleotide sequence and genetic organization of the gene cluster encoding the BoNT components poses a great challenge for the screening and characterization of BoNT-producing strains. Methodology/Principal Findings: In the present study, we designed and evaluated the performances of a resequencing microarray (RMA), the PathogenId v2.0, combined with an automated data approach for the simultaneous detection and characterization of BoNT-producing clostridia. The unique design of the PathogenID v2.0 array allows the simultaneous detection and characterization of 48 sequences targeting the BoNT gene cluster components. This approach allowed successful identification and typing of representative strains of the different toxinotypes and subtypes, as well as the neurotoxin-producing C. botulinum strain in a naturally contaminated food sample. Moreover, the method allowed fine characterization of the different neurotoxin gene cluster components of all studied strains, including genomic regions exhibiting up to 24.65% divergence with the sequences tiled on the arrays. Conclusions/Significance: The severity of the disease demands rapid and accurate means for performing risk assessments of BoNT-producing clostridia and for tracing potentials sources of contamination in outbreak situations. The RMA approach constitutes an essential higher echelon component in a diagnostics and surveillance pipeline. In addition, it is an important asset to characterise potential outbreak related strains, but also environment isolates, in order to obtain a better picture of the molecular epidemiology of BoNT-producing clostridia.