Pressure drop plays an important effect on the performance of fiber filter-stick, and is determined by the materials and geometry structure. In order to develop a method to design and guide the production of the fiber filter, the multiple regression method uses the density of fiber tow, length, and circumference of the sticker as the argument to train the pressure drop model based on the production data. The fiber filter is modeled as multizone represented as the fiber tow and the forming paper. The flow dynamics in these zones are simulated based on the porous media model. The osmotic coefficients represent the pressure drop in the zone packed with the fiber tow. The simulation results show that the pressure drop is positively correlated with the length of the fiber rob, and the type of filter tow has a greater influence on the pressure drop than the circumference. For the design of the fiber filter, the regression model is first used to obtain the consumption of the fiber tow based on the design pressure drop. Then the simulation based on the porous media model is carried out to validate the prediction. If the error between the two methods is within 10%, this predicted fiber stick can be produced. By analyzing the production data and the prediction from models, it is concluded that the method proposed in this work is sufficient to direct the design and production