The A-to-G point mutation at position 3243 in the human mitochondrial genome (m.3243A>G) is the most common pathogenic mtDNA variant responsible for disease in humans. It is widely accepted that m.3243A>G levels decrease in blood with age, and correction representing ~2% annual decline is often applied to account for this change in mutation level. Here we report that recent data indicate the dynamics of m.3243A>G are far more complex and depend on the blood mutation level in a bi-phasic way. As a consequence, the traditional 2% correction, which is adequate on 'average', creates opposite predictive biases at high and low mutation levels. Thus, overall accuracy of traditional correction depends on the proportion of individuals with high and low mutant levels in the dataset. Unbiased age correction is needed to circumvent these drawbacks of the standard model. We propose to abolish both biases by using an approach where correction depends on mutation level in biphasic way, to account for the biphasic dynamics of m.3243A>G in blood. The significance of removing bias was further tested using germline selection as a model, in which we detected mutation patterns consistent with the possibility of positive selection for m.3243A>G. We conclude that use of bi-phasic approach will greatly improve the predictive accuracy of modeling data for changes in mtDNA mutations in the germline and in somatic cells during aging.