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The past decade has witnessed a surging interest in the study of magnetic tactile sensors that can detect subtle changes in both normal and shear forces. However, due to the lack of guidance by appropriate theoretical models, the development of previous magnetic tactile sensors relies either on a trial‐and‐error manner or tedious point‐by‐point experimental calibrations, which are costly and time‐inefficient. Here, a theoretical model integrating magnetics, artificial neural networks, and nonlinear solid mechanics is proposed for the first time to guide the design of 3D magnetic tactile sensors. Then, a button‐shaped magnetic tactile sensor prototype that can detect subtle triaxial force changes is fabricated, which relates the nonlinear magnetic flux density to the external force, without burdensome calibration procedures. The sensor can achieve an axial measurement error of less than 1% and an in‐plane error of less than 3.7% with excellent durability. This study provides a comprehensive understanding of magnetic tactile sensors and sheds light on their applications in soft robotics, intelligent manipulation, and human–robot interaction (HRI).