Objective: To develop a nomogram model for preoperative diagnosis of proliferative hepatocellular carcinoma(HCC) based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced magnetic resonance imaging (MRI), and to explore its clinical value. Methods: MRI and clinical pathological data of patients confirmed by pathology as proliferative HCC (178 cases) and non-proliferative HCC (378 cases) between September 2017 and November 2022 who underwent preoperative Gd-EOB-DTPA enhanced MRI scans were retrospectively collected. The MRI features and clinical pathological characteristics of proliferative and non-proliferative HCC were evaluated. Multivariable logistic regression analysis was utilized to identify independent predictive factors for proliferative HCC, the R software was used to construct the nomogram prediction model, and its diagnostic performance was evaluated through receiver operating characteristic (ROC) curve. The calibration curve and decision curve analysis (DCA) were drawn to evaluate the calibration performance and clinical application value of the nomogram model. The optimal cut-off value was selected by calculating the Youden index to distinguish high risk and low risk. Kaplan-Meier survival curve was used to analyze the survival prognosis of proliferative and non-proliferative HCC, and log-rank test was used for comparison. Results: There were significant differences in AFP level(χ2=17.244, P<0.001), morphology of tumor(χ2=13.669, P<0.001), intertumoral fat(χ2=10.495, P=0.001), arterial phase peritumoral enhancement(χ2=37.662, P<0.001), tumor capsule(χ2=23.961, P<0.001), substantial intratumoral necrosis(χ2=77.184, P<0.001), intratumoral hemorrhage(χ2=4.892, P=0.027), peritumoral hypointense in hepatobiliary phase(χ2=47.675, P<0.001), rim arterial phase hyperenhancement(χ2=115.976, P<0.001), intratumoral artery(χ2=15.528, P<0.001) and venous tumor thrombus(χ2=10.532, P=0.001) between proliferative and non-proliferative HCC groups. Multivariate Logistic regression analysis showed that AFP>200 ng/ml(OR=0.640, P=0.044), no intertumoral fat(OR=1.947, P=0.033), substantial intratumoral necrosis(OR=0.480, P=0.003), peritumoral hypointense in hepatobiliary phase(OR=0.432, P=0.001), and rim arterial phase hyperenhancement(OR=0.180, P<0.001) were independent predictors of preoperative diagnosis of proliferative HCC. Based on the independent predictors, a nomogram model for preoperative prediction of proliferative HCC was established. The area under the ROC curve of the model for predicting proliferative HCC was 0.772 (95%CI: 0.735~0.807), the sensitivity was 69.1%, and the specificity was 75.4%. The calibration curve and DCA curve showed that the calibration performance and clinical applicability of the nomogram model were good. Kaplan-Meier curve showed that the survival rate of patients with proliferative HCC after hepatectomy was significantly lower than that of non-proliferative HCC (P<0.001), and the high-risk group was significantly lower than the low-risk group (P<0.001). Conclusions: The nomogram prediction model based on Gd-EOB-DTPA enhanced MRI imaging features combined with AFP >200 ng/ml can accurately diagnose proliferative HCC before operation and predict prognosis.