Small and Medium-sized Enterprises (SMEs) can enhance their performance and increase competitiveness through the utilization of smart technologies. However, selecting appropriate smart technologies is a problematic decision due to conflicting demands (such as interoperability versus cost) and inherent uncertainties. The current study develops a comprehensive decision support framework for the selection optimal smart technologies in SMEs. The suggested model is a tripartite model involving: (1) recognition and validation of key indicators, (2) analysis of causal relationship and weighting through Fuzzy Interpretive Structural Modeling (FISM) and Fuzzy DEMATEL (FDEMATEL), and (3) technology ranking through an Adaptive Neuro-Fuzzy Inference System (ANFIS) integrated with a hybrid optimization algorithm and Type-2 Fuzzy Analytic Hierarchy Process (Type-2 Fuzzy AHP). Data were gathered by interviewing 15 SMEs and surveying 10 experts using questionnaires. Results indicated that among 12 indicators, "compatibility with existing processes," "return on investment," and "information security had the most significant impact. The Type-2 Fuzzy AHP and hybrid ANFIS model gave the best performance with accuracy of R2=0.956 in nonlinear relationship capturing and ranking alternatives under conditions of uncertainty. Framework robustness was confirmed by scenario analysis (optimistic, probable, and pessimistic), and technology rankings were stable in all scenarios. Results indicated that Internet of Things (IoT), blockchain, and artificial intelligence were found to be the most appropriate alternatives for the SMEs under investigation.