Abstract: Mitochondrial DNA disorders – disorders associated with dysfunctions of the oxidative phosphorylation system (OXPHOS) – are caused by inborn metabolism errors and have an estimated frequency of 1 out of 10000 live births. Due to the relevant role played by the OXPHOS system in ATP production, causes and effects of mitochondrial disorders are highly heterogeneous and complex. Major origin of mitochondrial disorders is in both nuclear and mitochondrial DNA mutations. Although prenatal diagnosis is routine for nuclear DNA mutations, the cases of prenatal diagnosis of mtDNA mutations are rare, even though urgent, as no real therapies exist. However thanks to bioinformatics support, the gap may be reduced in a short time. Indeed, up to now, the pathogenicity of mtDNA mutations has been, in most cases, prevalently validated by their segregation with the disease and their consequent loss of function when the mutation involves a structural gene, but no systematic statistical analysis of the mtDNA SNPs has been performed. Moreover the criteria commonly followed to associate a mutation to a given pathology are: - aminoacidic change in a strictly conserved site; - presence in patients only; - heteroplasmy condition; - presence in phenotipically similar, but ethnically different families. However a strict correlation mutation-phenotype in patients is not always verified. Here we propose a statistical approach aimed to contribute in the estimation of the pathogenic variation sites. The analysis is based on the estimation of site-specific relative variability in a sets of homologous sequences, through the application of SiteVarProt and SiteVariability softwares, in order to infer a correlation between site variability and pathogenicity of a given mutation.