This work aims at the development of a method based on FT-NIR spectroscopy and multivariate analysis for the identification and quantification of minced beef meat adulteration with turkey meat. Samples were analyzed as raw, frozen-thawed and cooked. Different multivariate regression and class-modeling strategies were evaluated. PLS regression models with R² in prediction higher than 0.884 and RMSEP lower than 10.8% were developed. PLS-DA applied to discriminate each type of sample in two classes (adulteration threshold = 20%) showed values of sensitivity and specificity in prediction higher than 0.84 and 0.76, respectively. Thus, the study demonstrates that FT-NIR spectroscopy coupled with suitable chemometric strategies is a reliable tool for the identification and quantification of minced beef adulteration with turkey meat not only in fresh products, but also in frozen-thawed and cooked samples. This achievement is of crucial importance in the meat industry due to the increasing number of processed meat products, in which technological treatments can mask a possible inter-species adulteration.