Outcomes with a natural order commonly occur in prediction problems and often the available input data are mixture of complex like images tabular predictors. Deep Learning (DL) models state-of-the-art for image classification tasks but frequently treat ordinal outcomes as unordered lack interpretability. In contrast, classical regression consider outcome’s yield interpretable predictor effects ...