Hoarding is a complex and impairing psychiatric disorder and a public health problem. Traditionally it is assessed through observation and interview, but recently a new method has been proposed where living quarters of an individual are visually compared with a set of template images ranked according to the “Clutter Image Rating” (CIR) scale from 1 to 9. However, such an assessment is time-consuming, subjective, and weak in repeatability. We propose an automatic method for classifying hoarding images according to the CIR scale. Since clutter in living quarters (e.g., piles of boxes, newspapers, clothing) corresponds to “busy” areas with lots of edges in captured images, we use the histogram-of-gradients (HOG) descriptor to characterize images and estimate the CIR value using two methods: regression and classification. In 4-fold cross-validation on 620 images that we harvested from the internet, both methods result in mean-absolute CIR error of about 1.2. Given the simplicity of our method, this is an encouraging result as it approximates ratings by trained professionals who admit assigning CIR values within ± 1 CIR point.