Our aim is to propose a model-free approach to decision making that is based on the direct use of images. More, precisely, a content of each image is used – without further processing – in order to cluster them by the K-medoids method. Then, decisions are attached to each cluster by an expert. When a new image is acquired, it is firstly classified to one of the clusters and the corresponding decision is made. The approach is conceptually rather simple, but its success in on-line applications depends on the way of organizing learning and decision phases. We illustrate the approach by the example of a decision-making system for industrial gas burners.