Monitoring complex systems includes scanning, aggregating and processing data from various sources. The design of graphical interfaces for monitoring tasks involves a fine-grained exploration of the importance and expected frequency of events that an operator needs to be informed about.The Human Efficiency Evaluator is a tool for the prediction of human behavior. We extended it to predict the distribution of operator’s attention while monitoring interfaces. The prediction is based on the SEEV model. We show that our tool can be used by experts with different backgrounds to generate predictions following a structured, semi-automated process.In a qualitative study with subject matter experts, we analyzed different HMI designs for a navigation task in the maritime domain. We evaluated their modeling time, tested different prediction result visualizations, and investigated in the model differences between the subjects. Different to what we originally expected, the study revealed that the models created by the subjects substantially differ depending on their perspectives. Heat maps visualizing the predicted attention allocation were appreciated by the subjects and enabled them to argue about their perspective.