As a third-generation semiconductor material, indium phosphide (InP) exhibits complex anisotropic etching characteristics, showing significantly varying etching morphologies under different temperature, concentration, and surfactant conditions. This complexity poses challenges in controlling the etching evolution process and predicting its three-dimensional structures. To address the simulation of InP etching structures and surface morphology, this study first establishes an atomic model of the InP etching system and analyzes how different atomic structures influence crystal plane etching rates. Subsequently, based on the microscopic activation energy theory, we propose an atomic removal determination function (InP-RPF) for InP etching substrates, numerically elucidating the relationship between macroscopic crystal plane etching rates and microscopic atomic removal probabilities. Furthermore, we develop an evolutionary Monte Carlo etching system model (InP-EMC), employing evolutionary algorithms to continuously optimize the energy parameters in the InP-RPF function, thereby adjusting the removal probabilities of various atomic types on the substrate and validating the simulated etching rates. Experimental comparisons demonstrate that the InP-EMC model accurately constrains atomic removal probabilities using limited crystal plane etching rate data, achieving simulation accuracy exceeding 90% for full-crystal-plane etching rates, mask etching structures, and surface morphology characteristics.