Cyber threats are becoming more frequent and complex, making decision systems crucial to cybersecurity. The review paper uses machine learning to examine decision systems and cybersecurity, highlighting its fundamentals, applications, and challenges. The paper begins with a detailed cybersecurity overview, emphasizing the need for strong decision-making systems to address changing threats. We define and discuss decision systems in the fundamentals section, emphasizing their importance in cybersecurity. An analysis of cybersecurity decision system development highlights significant achievements and technological progress. This paper focuses on machine learning in cybersecurity decision systems. Analyzing cybersecurity machine learning methods allows for a thorough examination of their use in decision-making. We discuss the pros and cons of integrating machine learning into decision-making systems and its impact on cybersecurity. Intrusion Detection Systems (IDS), Threat Intelligence Platforms (TIP), Incident Response and Management, and Adaptive Security Architectures are examined in the methods and processes section. Each system will be examined for its function, machine learning algorithms, and case studies to demonstrate their practicality. Assessing decision system effectiveness requires metrics and benchmarks. This paper analyzes decision system performance metrics and cybersecurity machine learning model benchmarks and datasets. Using these metrics to compare decision systems reveals their strengths and weaknesses. The review concludes with future machine learning-based decision system challenges and new trends and technologies. To maintain cybersecurity resilience, recommendations are made to address future challenges and improve decision-making systems. In-depth machine learning analysis in this review paper expands cybersecurity decision system knowledge. This resource helps researchers, practitioners, and policymakers understand, implement, and improve cybersecurity decision systems in a changing threat environment.