Mitochondrial DNA (mtDNA) variation is commonly analyzed in a wide range of different biomedical applications. Cases where more than one individual contribute to a stain genotyped from some biological material give rise to a mixture. Most forensic mixture cases are analyzed using autosomal markers. In rape cases, Y-chromosome markers typically add useful information. However, there are important cases where autosomal and Y-chromosome markers fail to provide useful profiles. In some instances, usually involving small amounts or degraded DNA, mtDNA may be the only useful genetic evidence available. Mitochondrial DNA mixtures also arise in studies dealing with the role of mtDNA variation in tumorigenesis. Such mixtures may be generated by the tumor, but they could also originate in vitro due to inadvertent contamination or a sample mix-up.We present the statistical methods needed for mixture interpretation and emphasize the modifications required for the more well-known methods based on conventional markers to generalize to mtDNA mixtures. Two scenarios are considered. Firstly, only categorical mtDNA data is assumed available, that is, the variants contributing to the mixture. Secondly, quantitative data (peak heights or areas) on the allelic variants are also accessible. In cases where quantitative information is available in addition to allele designation, it is possible to extract more precise information by using regression models. More precisely, using quantitative information may lead to a unique solution in cases where the qualitative approach points to several possibilities. Importantly, these methods also apply to clinical cases where contamination is a potential alternative explanation for the data.We argue that clinical and forensic scientists should give greater consideration to mtDNA for mixture interpretation. The results and examples show that the analysis of mtDNA mixtures contributes substantially to forensic casework and may also clarify erroneous claims made in clinical genetics regarding tumorigenesis.