Abstract: Muddy terrains present significant challenges for terrestrial robots, as subtle changes in composition and water content can lead to large variations in substrate strength and force responses, causing robot to slip or stuck. This paper presents a method to estimate mud properties using proprioceptive sensing, enabling a flipper-driven robot to adapt its locomotion through muddy substrates of varying strength. First, we characterize mud reaction forces through actuator current and position signals from a statically-mounted robotic flipper, and use the measured force to determine key coefficients that characterize intrinsic mud properties. The proprioceptively estimated coefficients match closely with measurements from a lab-grade load cell, validating the effectiveness of the proposed method. Next, we extend the method to a locomoting robot, to estimate mud properties online as it crawls across different mud mixtures. Experimental data reveals that mud reaction forces depend sensitively on robot motion, requiring joint analysis of robot movement with proprioceptive force to correctly determine mud property. Lastly, we deploy this method in a flipper-driven robot moving across muddy substrates of varying strengths, and demonstrate that the proposed method allow the robot to use the estimated mud properties to adapt its locomotion strategy, and successfully avoid locomotion failures. Our findings highlight the potential of proprioception-based terrain sensing to enhance robot mobility in complex, deformable natural environments, paving the way for more robust field exploration capabilities.