An exploration of riskit analysis graph (RAG) as a major technique of Riskit method is presented in this work with the aim of enhancing its capability for better risk identification (and management) and subsequently, contribute to software delivery time. The study begin with a brief background of the riskit as a major tool in risk analysis; pointing to the need for an enhancement of the tool and associated benefits plus disadvantages. After this, a review of closely related works in the field of study is presented leading to identification of some perceived limitations and challenges in the generic Riskit methods (RAG inclusive).Next, an analysis of a typical riskit analysis graph process vis-à-vis its main components is presented. Using the stepwise approach to risk profiling, a prototype of the intended model called the “enhanced risk analysis model-ERAM”-is presented based on risk ontology and prognosis states. The ERAM was developed in phases through leaning on the basic approach of risk models which comprises of a generic four steps –establishing the likelihood of occurrence of risks in the task pool, identification of major variables for measuring the impact (should it occur); a computer simulation is performed leading to a well defined risk profile and finally, a conclusion was drawn on the fact that Riskit can actually be extended through a deep analysis of it process components.