This paper introduces a novel Pythagorean fuzzy pattern recognition- (PFPR) model for the evaluation of the Social Inclusion Index (SII) in Azerbaijan, a crucial component of the Social Quality framework. The approach takes into account the fuzziness of input data and the fuzziness generated throughout the computation process, utilizing Pythagorean fuzzy (PF) logic tools. The proposed model integrates operations framing the PFPR process. Compared to existing multiple-criteria decision-making methods, the contemplated algorithm enhances the computation of socio-economic indices. The paper explores the multidimensional nature of social inclusion, emphasizing its role in creating equal opportunities and facilitating engagement across various societal spheres. To measure social inclusion, the study addresses challenges related to defining social inclusion and identifying indicators, drawing on approaches from institutions such as the European Commission and Eurostat. The results obtained reveal the SII level in Azerbaijan, and the proposed approach demonstrates its applicability in analyzing and estimating various socio-economic phenomena.