Abstract
In software development project management, Risk management represents critical knowledge and skills at the level of a single software project and at the enterprise level, which executes multiple software projects concurrently. The best decision of Risk management contributes to optimizing resource allocation at the enterprise level for achieving its goals. Therefore, the issue needs centralized risk management at the enterprise level as a whole and not for each project. Risk management is implemented through several stages and using different methods. Various studies deal with multiple aspects of software management. This research provides an analytical view of risk assessment in multi-environment software development projects that take place simultaneously. The study uses a public dataset previously used in previous research for several simultaneous projects in one organization. It describes the multi-software project's risks through 12 variables. A comparative analysis uses classification methods (Random Forest- TreesJ48 - REP Tree - Simple Logistic) to assess risks and put them in central view. The research experiment has proven high accuracy in determining risk levels in a multi-project environment, reaching approximately 98%, using the REP tree technique.