The ore-forming numerical modeling has greatly advanced our understanding of several geological processes (e.g., structure deformation, fluid flow) and their relation to ore deposit genesis [36; 37; 38; 39; 40; 41; 42; 43; 44]. For instance, [PERSON] et al. [38; 45; 46; 47] employed computational modeling to uncover the influence of rock difference, dip variation, and strain localization on fluid flow patterns in the structural-controlled, uncomformity-related uranium system in the Athabasca Basin, Canada. Additionally, numerical modeling can also simulate temporal-spatial metal precipitation or rock stress geodynamics to delineate the fluid pathways and traps to locate potential mineralization. For example, [PERSON] et al. [13], [PERSON] et al. [48], and [PERSON] et al. [49] used the dilation space, mineralization rate, and/or geochemical interaction as ore proxies to find the favorable metal deposition location at depth. [PERSON] et al. [50] and [PERSON] et al. [51] discussed the fault geometry controls on the rock deformation and fluid flow regular pattern and determined the mineralization exploration strategies in strike-slip fault fluid systems. Thus, ore-forming numerical modeling has the powerful ability to provide ore-predictive information in terms of the metallogenic geodynamic system. These data, together with model spatial features, are promising to enhance 3D mineral prospectivity models. The Jiaodong Peninsula is the largest gold province of China, boasting more than 5000 tons of Au resources (Figure 1) [52]. Gold deposits in this region show similar geology and mineralization characteristics with orogenic gold deposits, of which the regional fault control orebody localizations are ubiquitous and lack the gold affinity for lithology [53; 54; 55; 56; 57; 58; 59; 60; 61; 62]. In terms of relatively simple geological characteristics, these conditions provide an excellent study objective for performing 3D-model analysis and numerical modeling. However, few previous studies have conducted systematic and comprehensive research from spatial and temporal perspectives to investigate these gold deposits and guide deep exploration. Herein, we selected the Xiadian gold deposit as a case study to perform 3D MPM with the integration of ore-forming computational simulation information to examine the added geodynamic variables' effects on prediction results. This research aims to provide a new way to uncover more predictor variables for 3D MPM, gain new insights into the controls on gold mineralization, and identify mineral resources responsibly and efficiently. The rest of this paper is structured as follows. Section 2 presents the geological background of the Xiadian deposit. In Section 3, we introduce the dataset used in the case study and describe the methodologies employed for 3D modeling, feature extraction, ore-forming simulation, and prospectivity modeling. In Section 4, we first detail the modeling and simulation outcomes and further discuss the differences between the three models based on different variable sets. Section 4 concludes by presenting the target appraisal facilitated by the prospectivity model. Finally, Section 5 summarizes the contributions made by this paper.