This research paper presents a real-time fraud prevention system that integrates Artificial Intelligence(AI), Explainable AI (XAI), and blockchain technology through a framework called ProofLedger. The systemis designedtoaddress limitations of traditional fraud detection methods, such as lack of adaptability, transparency, and secure record-keeping. It uses machine learning models to detect fraudulent transactions and generates interpretable explanations usingXAI techniques, enabling better understanding and trust in automated decisions. To ensure data integrity and auditability, all critical transactions and decisions are stored in a tamper-proof blockchain ledger. The system follows a modular architecture consisting of components such as an AI fraud detection engine, decisioncontroller, explainability module, and blockchain framework. It processes transactions in real time, combiningpredictiveanalytics with rule-based validation to improve detection accuracy. Experimental analysis demonstrates that the system is efficient, reliable, and capable of maintaining transparency and traceability. Overall, the proposed solution enhances fraud detection by providing secure, explainable, and scalable mechanisms suitable for modern financial systems and digital platforms. Keywords: Fraud Detection, Artificial Intelligence (AI), Explainable AI (XAI), Blockchain, ProofLedger, Real-Time Systems, Machine Learning, Data Security, Auditability, Financial Transactions