Recently, declarative process modeling have gained a wide attention from both industry and academia to model loosely-structured processes, mediating between flexibility and sup-port. Instead of describing step by step in an imperative way the set of activities to perform (e.g., Petri-net, UML Activity, BPMN), declarative languages define constraints between the process activities that must not be violated during the execution. Even if these languages allow for a high degree of flexibility, this freedom leads to some understandability problems. Indeed, having a mental representation of the pos-sible process executions becomes too complex for humans as the number of constraints increases on the model. This paper presents a novel and formal approach to automati-cally synthesize execution plans of declarative processes. At design-time, the plans can increase the understanding and the confidence in the model by providing an early and direct experience with it while being modeled. At run-time, the planning component is primordial to ensure that an execution may still lead to a desired goal by giving the possible execu-tion traces leading to it. A working implementation based on the Alloy model-finding method [10] has been developed. The evaluation of this implementation showed us that plans can be generated efficiently and quickly.