Research reactors are deemed manifold-roles environments that perform the various tasking of training, research, and commercial goals. And this is even though it contains risks and possible sources of harm. Therefore, reactor managers have to make accurate and appropriate decisions at the right time, based on little available knowledge. Few articles review this hazardous environment and industries' risks as well as human and environmental consequences and how can ensure human control in these critical environments. Since the beginning of the research reactors, operation Decisions concerning planning and management have represented a major concern for decision-makers in this field. International organizations (IAEA Safety Principles, 2006 & IAEA, 2007) have identified the importance of accurate planning and the Fundamental Safety Principles which are necessary and critical to the operation of nuclear facilities, dealing with human resources, supplies, and materials, as well as to radioisotope produce requested, training and, research constraints. In this research, a framework is proposed for combining IAEA Safety Principles and Risk Assessment process for helping manage risks, making decisions, determine and achieving goals, and perfecting performance for these critical facilities. The neural network can be subjected to verdict the priorities risks and to calculate the weight factors that must be taken into account in the decision- making process.For Clarification of the proposed framework performance the case study was conducted on a real-world for Research Reactor.