The studies on software project failures have identified problems in capturing requirements, managing complexity and dynamic changes of the environment because of the using traditional software engineering, where requirement capturing is static and prolonged. This issue is especially important for decision-making in dynamically changing business. The paper offers modernization of information system development methods used for implementation of automated information-, rule-, knowledge-, model-based decision processes. The paper propose to assist processes by early separation and development of a business logic model and implementation of decision-making, knowledge discovery process models and business process analysis using probabilistic models by proposing an information systems development framework. The advantages of such approach are early separation and development of a business logic model and further support for business people for modification of business logic without involvement of software developers and minimizing their persistence in the latter exploitation stages. Finally, the paper presents experimental results for stochastic decision extraction from system database using process mining and probabilistic models to ease framework implementation.