In the contemporary era, algorithms have moved beyond their role as mere computational tools and are progressively entering the domains of regulation and lawmaking. Through their pervasive embeddedness in governance infrastructures, they are emerging as de facto “silent lawmakers” whose normative force can shape new social and legal orders. This development confronts legal systems with unprecedented challenges. Against this backdrop, the present study aims to clarify the legal nature of algorithmic regulation and to propose a structured framework for addressing the challenges arising from the growing influence of algorithms within systems of governance. Accordingly, the central research question is how an effective legal framework for algorithmic regulation can be designed that is responsive to technical complexities while preserving the fundamental principles of the rule of law. The study proceeds from the premise that regulating algorithms requires a shift from traditional legal frameworks toward approaches that employ technology itself as a regulatory instrument. Methodologically, the research adopts an analytical descriptive approach, drawing on library based research, the analysis of legal instruments, and the examination of judicial decisions. The findings indicate that algorithms, beyond their instrumental role, possess normative and regulatory capacities. Existing legal frameworks are therefore insufficient to address this phenomenon, which underscores the need for innovative approaches such as data driven regulatory infrastructures, algorithmic auditing, regulation by design, and adversarial machine learning. These strategies help to reconcile technological efficiency with legal constraints and outline a pathway for preserving the rule of law in the age of artificial intelligence.