Abstract: The present invention provides for a system and a method for optimized predictive risk assessment of software development lifecycle of projects. The present invention provides for fetching an unstructured attribute dataset and grouping the unstructured attribute dataset based on derived Knowledge Performance Indicator (KPI) scores. The present invention provides for converting the unstructured attribute dataset into a structured attribute dataset by applying pre-defined rules, where each attribute data of the structured attribute dataset is mapped to pre-determined categorical values. The present invention provides for correlating a derived attribute data from the structured attribute dataset with a defined attribute data to derive an accuracy percentage. The present invention provides for combining the KPI scores, the accuracy percentage and the spillover risk values and the defect density values for risk assessment in the software development lifecycle of projects to generate indicators of risks.