The fundamental goal of forensic genetics is personal identification but it is common to obtain inconclusive results from both direct and indirect STR-profile comparisons. In such cases, it is necessary looking for alternative approaches to generate crucial forensic leads and identify unknown perpetrators. In this thesis, we propose alternative tools to predict BioGeographical Ancestry (BGA) and to identify males sharing the same Y-haplotype by utilizing multivariate techniques and Rapidly Mutating Y-chromosome short tandem repeats(RM Y-STRs), respectively. Concerning ethnic inference, we proposed novel statistical approaches (consisting in SLPCA, PLSDA and SVM methods) to group samples into BGA-classes, by testing both autosomal STRs (in African populations) and microhaplotypes (in U.S. populations). The predictive power of such statistics resulted extremely high; in fact, they enhance cluster separation providing misleading classifications for genetically mixed populations only. As to Y haplotype discrimination improvement, we proved the efficiency in individualization power of RM Y-STRs – reaching a total of 48 markers genotyped – in African populations characterized by high levels of endogamy, patrilinearity and population structuring. Together, these two innovative approaches converge in demonstrating they represent powerful tools to maximize the information inferable from biological evidence collected at the crime scene
