With more than 30 percent of the country's population residing in rural areas and experiencing the consequences of climate change, resource depletion, and social inequalities, strengthening the role of local councils has become essential. Sustainable development is not determined solely by natural or economic resources; it also depends on effective management capabilities. solving these challenges requires a comprehensive approach to development-particularly digital transformation in management. This study aimed to present a theoretical-algorithmic model of the effectiveness of local councils in sustainable rural management based on artificial intelligence. The research is interpretive-critical paradigm, developmental-applied, descriptive-survey, and mixed. The statistical population in qualitative section was articles were 25 selected using the scoping review method. The data collection tool was checklists of selected codes according to the three basic models. Themes were identified using thematic analysis technique. The validity and reliability of the codes were confirmed. The statistical population in quantitative section was village heads and local councils members of Mazandaran province. 20 council members were selected purposefully and conveniently. Data were collected through researcher-made questionnaire, field data, and secondary data from 20 available villages. The content validity of the questionnaire was confirmed with CVR and CVI value indices, and the construct validity was confirmed through confirmatory and exploratory factor analysis, and reliability was confirmed with Cronbach's alpha test. Using artificial intelligence algorithms (neural network, multi-criteria analysis, fuzzy regression), focusing on the three axes of sustainable management (smart agriculture, water resources management, renewable energies), quantitative modeling and prediction of sustainable rural management patterns in these three axes were performed. The quantitative model validity was confirmed. The theoretical model included 4 organizing themes, 10 basic themes, and 28 codes. The theoretical model showed that the efficiency of councils is improved by strengthening the 4 functions of decision-making, forecasting, strengthening participation, monitoring, and evaluation. These 4 functions can be strengthened by taking advantage of the opportunities created by artificial intelligence. The algorithmic model showed that, from the perspective of villagers and councils, water resources management is a priority over smart agriculture and renewable energy. The results of this study showed that artificial intelligence can significantly increase the efficiency of local councils in sustainable management. These results, while being in line with the results of previous research, provided a native model by combining two theoretical and algorithmic models. This model created a link between management and technological concepts, which led to the presentation of an integrated model that, compared to the traditional management method that village heads and councils previously had, can provide more accuracy and comprehensiveness to their decisions and performance for providing rural services, especially water resources management.