The work aims to improve the processing quality and efficiency of silicon nitride ceramics, the prediction accuracy of the roughness model. The critical depth of plastic and plastic-brittle removal transition hc1, critical depth of plastic-brittle and brittle removal transition hc2 were proposed. Secondly, the original model was modified. The roughness correction coefficients of the plastic removal φ1 and τ1, the roughness correction coefficients of the plastic-brittle removal φ2 and τ2 were introduced. A roughness prediction model based on different removal methods was established. Finally, the coefficients were solved by grinding experiments. The effect of grinding parameters on roughness and surface topography were obtained. The results show that the roughness correction coefficients of the plastic removal φ1 =5.872×10–6, τ1=0.1094. The roughness correction coefficients of the plastic-brittle removal φ2 =1.299×10–5, τ2=0.1582. When the grinding wheel speed vs increases from 30 m/s to 50 m/s, the roughness Ra decreases from 0.366 μm to 0.266 μm. The removal method changes from brittle fracture to plastic deformation. And the surface quality becomes better. When grinding depth ap increases from 5 μm to 45 μm, the roughness Ra increases from 0.252 μm to 0.345 μm. The removal method changes from plastic deformation to brittle fracture. And the surface quality deteriorates. When workpiece feed rate vw increases from 1000 mm/min to 9000 mm/min, the roughness Ra increases from 0.227 μm to 0.572 μm. The removal method changes from plastic deformation to brittle fracture. And the surface quality deteriorates. The relative error between the model predictive value and the experimental value δ is 2.1%~8%. The conclusion is that the grinding depth and the workpiece feed speed should be controlled during the machining. And the grinding wheel speed should be properly increased to ensure the machining accuracy and efficiency. The roughness prediction model based on different removal methods can accurately predict actual machining conditions.