Administrative corruption, as one of the fundamental challenges in governance systems, has devastating effects on public trust, economic development, and social justice. This study presents a model for utilizing blockchain technology to increase transparency and reduce administrative corruption using the Interpretive Structural Modeling (ISM) approach. The research was conducted using a mixed-methods approach (qualitative-quantitative) and employed content analysis and ISM. Data were collected through a systematic literature review and expert surveys. The validation of the method was carried out through theme review by four experts, calculation of inter-coder agreement coefficient (0.83), and final model approval by a specialist panel (with an agreement level of 85%). The findings indicate that the unique features of blockchain, such as immutability, transparency, and decentralization, can serve as effective tools for reducing corruption. The model proposed in this study comprises five main levels: infrastructural (decentralization, security, and immutability), technological (digital identity and smart contracts), regulatory (financial monitoring and internal controls), organizational (accountability and collaboration), and social (public participation and education) levels. The results suggest that implementing blockchain can facilitate the reduction of corruption through process automation, elimination of intermediaries, and increased accountability. Moreover, this study examines the technical, financial, and cultural challenges related to blockchain adoption and offers solutions to address them. Finally, policy recommendations are provided for policymakers to leverage this technology towards transparent and efficient governance.