Nearly half a million project managers execute about a million software projects every year all around the world, turning out software worth more than $600 billion. A considerable part of the software projects, as one of the studies, Standish Group report shows nearly three - quarter of over all as challenged or cancelled, goes in vain due to unhandled damaging project risks associated with them.Most of them are unidentified until too late to manage them and the results of these project have been nothing but desperate cancellation. Henceforth, it goes without saying the need of risk identification which is a core process of risk management, the most crucial management in any project management.Software risk is a measure of the chance and loss of an unacceptable result disturbing the software project, software process, or software product.Each software system is distinctive with its own particular set of risks. There are many software risks but fewer consequences that we care to avoid. Mostly, it is hard to avoid all kinds of risks in a project. This is why we often care about a few highly impacting risks like potential cost, schedule, technical consequences in any project. These software risks could avert a software project from meeting its cost, schedule, and technical objectives. Software risk is hazardous because it can prevent software project success.Software risk identification is the initial process in the risk assessment which is a part of risk management. Without proper risk identification, it is tough to control and manage the risk that is associated with the software project. So far, a number of research papers are contributed to this effort and a vast majority of techniques have been applied for the concerned problem to solve the issue but still most of them are basically, depend on rigorous textual procedures to identify risks.The current work is an innovative attempt to solve the software project risks identification problem with KeyGraph, a graphical tool of chance discovery. This procedure, in turn, simplifies the software risks identification and consolidates attempts to identify software risks more vivid and robust fashion.Further, the procedure enhances human ability and endeavour to identify software risks by analytic capabilities. At the same time, it is important to bear in mind that the procedure consists an analytical approach that’s what we call human initiative, the human process of externalizing the tacit experiences, rather than, an autonomous or machine-dependent one.The software risk identification process begins with the creation of software project risk scenarios. These scenarios are at first, made by collecting essential set of data or nodes as input to the formation of KeyGraph.Further, co-occurrence network is created by links between these frequent co-occurring item-pairs or node-pairs of the data-set. The fundamental islands are obtained by deleting links that separates the graphs and deleting the links of highest contribution. This situation is regarded as generation of hubs, candidates of rare event or chance, indeed, risks which are significant items, touching many node-cluster bridges of frequent co-occurrence. A deliberate analysis is done before the nomination of these risks. Finally, these risks are nominated with the aid of software risk categorization.