Autism spectrum disorder (ASD) is a neurodevelopmental condition occurring in 1:77 Italian children. Several comorbidities are reported, including functional gastrointestinal disorders (FGIDs) present in up to 70% of patients. FGIDs are disorders resulting from a combination of symptoms affecting motility, hypersensitivity, and other functions, which are not caused by anatomic or organic origin and that impact the severity of ASD core symptoms and complicate the clinical management of ASD children, especially those who are non-verbal. Evidence reports gut microbiome (GM) remodelling in ASD children, and postbiotic butyrate, a GM-derived metabolite, attenuates FGIDs in children and restores social behavior in ASD mouse models. Clinical data on butyrate effects in ASD are still scanty. The present study investigates the therapeutic effects of a 16-week oral postbiotic supplementation on clinical/behavioral profiles, gastrointestinal disturbances, gut microbiome, and immune and inflammatory biomarkers in peripheral blood and fecal samples in children with ASD and FGIDs. Using the Machine Learning (ML) approach, a subset of artificial intelligence, this study also aims to identify predictive factors implicated in the effect of the postbiotic supplementation on FGIDs, important for prevention through modulation of the microbiota. The investigators expect that treating FGIDs will have an impact on the behavioral and core symptoms of ASD and the quality of life of children and their families.