In order to optimize the optimal combination screening method of laser processing parameters in the early stage of laser processing surface bionic texture of reciprocating pump plunger, a laser engraving texture experiment on the surface of the plunger was carried out. Based on the experimental data, a BP artificial neural network prediction model between laser parameters and texture volume was established and successfully trained. The results show that the effects of laser power, travel speed, and scanning pass on the texture volume are mutually independent and equivalently related. Also, the average prediction accuracy of the three-layer BP neural network model with 4 neurons in the hidden layer is about 92%. Based on the forward prediction of laser parameters to texture volume, this research is of great significance for the industrial batch application of bionic texture technology on the surface of fracturing pump plunger.