A study reveals a new machine learning method to predict shear forces at the body-seat interface, which are key contributors to pressure injuries. Utilizing data from pressure mapping systems and a customizable experimental seat, researchers developed a Random Forest Regression model. This model was trained on data from individuals without disabilities and tested on both them and wheelchair users. It used six input features: a calculated variable, backrest force, feet normal force, seat pan force, backrest area, and the location of the backrest center of pressure. The model achieved an average error of less than 20% for both groups, but its accuracy decreased for wheelchair users with significantly lower shear forces. Future research will aim to enhance the model’s effectiveness by including a more diverse participant pool with varying physical characteristics and seated postures.