Abstract: This study aimed to elucidate the mechanism underlying the influence of cigarette porosity on dynamic resistance. Through the quantitative analysis of the correlation between the static porosity of the characteristic regions and the dynamic resistance, a predictive modelhas been established. The three-dimensional pore characteristics of the cigarette rods were obtained using micro-CT imaging technology. Within each 60-second suction interval, the cigarette in the burning state were divided into four characteristic regions: the burned section, the burning section, the smoking-burning section, and the remaining section. Combining dynamic resistance collected via its testing system, the correlation characteristics between porosity and dynamic resistance across various characteristic sections were analyzed. Based on the fourth-order response surface method, mathematical models for static porosity and dynamic resistance across characteristic sections were established, with parameter optimisation achieved through a particle swarm optimisation algorithm.The porosity of the smoking-burning section had the most significant impact on the dynamic resistance of the cigarette rod, with an average Pearson correlation coefficient of -0.86, showing a strong negative correlation; the influence of the static porosity of the remaining section was weaker, with an average correlation coefficient of -0.54. Based on the established mathematical model, the average relative deviations between the actual and predicted resistance for specifications C, D, Z, and X are 2.80%, 2.32%, 2.59%, and 2.76% respectively, indicating that the predictive model exhibits high precision.This study analyzed the intrinsic correlation between the pore characteristics of cigarette and the dynamic resistance partially. The established mathematical model provides a quantitative basis for the digital design of cigarette products.