Human experience is rich with sensory information, from which physical regularities are internalized to guide behavior. This paper presents the Patchwork Approach, a method for modeling sensorimotor predictions based on these regularities, without explicitly encoding physics. This method leverages environmental regularities, enabling resource-rational perceptual predictions. Using data from previous studies (Deeb et al., 2021, 2024) on human perception, the model outperforms Newtonian-based models in capturing human prediction errors and interpolates across untested conditions. One test demonstrates its superiority in a projectile motion task, while another illustrates its ability to predict deflection angles in a collision event from untrained aiming angles. This approach provides valuable insights into how physical laws are internalized and used to guide perception and action–arguing that perception provides foundational input to intuitive physics reasoning, a role that can complement and be extended to higher-level cognitive processes like those explained by the Intuitive Physics Engine (IPE).