This paper advocates for the introduction of performance awareness in autonomic systems. The motivation is to be able to predict the performance of a target configuration when a self-* feature is planning a system reconfiguration. We propose a global and partially automated process based on queues and queuing networks models. This process includes decomposing a distributed application into black boxes, identifying the queue model for each black box and assembling these models into a queuing network according to the candidate target configuration. Finally, performance prediction is performed either through simulation or analysis. This paper sketches the global process and focuses on the black box model identification step. This step is automated thanks to a load testing platform enhanced with a workload control loop. Model identification is then based on statistical tests. The model identification process is illustrated by experimental results.