Workflow systems are being used by business enterprises to improve the efficiency of their internal processes and enhance the services provided to their customers. Workflow models are the fundamental components of Workflow Management Systems used to define ordering, scheduling and other components of workflow tasks. Companies increasingly follow flexible workflow models in order to adapt to changes in business logic, making it more challenging to predict resource demands. In such a scenario, knowledge of what lies ahead i.e., the set of tasks that are going to be executed in the future, assists the process administration to take decisions pertaining to process management in advance. In this work, we propose a method to predict possible paths of a running instance For instances that deviate from the workflow model graph, we propose methods to determine the characteristics of the changes using classification rules.