Abstract: The quantitative prediction of petrophysical properties is crucial to resources assessment and development planning for shale reservoirs. The rock physics template (RPT) serves as a key tool to link these properties to elastic responses and is therefore widely applied to the quantitative inversion of critical reservoir properties. However, the complex mineral composition and pore structures of shale oil reservoirs compromise the accuracy of traditional model-driven RPTs in the inversion. Consequently, their predictive capacity often falls short of exploration and development demands. To address this issue, we propose a 3D RPT generation approach that incorporates both data and model constraints for the quantitative prediction of sensitive petrophysical parameters. We first tailor a rock physics model to achieve the accurate prediction of shear velocity and equivalent pore aspect ratio for the target area. This model is subsequently used for the perturbation and sensitivity analyses, which ultimately identify three key petrophysical parameters most sensitive to elastic responses: calcite content, porosity, and pore aspect ratio. Under the constraint of the rock physics model, we establish an RPT to reflect the macroscopic relationship between petrophysical and elastic parameters. The RPT is further enhanced by incorporating log data via the radial basis function (RBF) interpolation method, resulting in a high-precision 3D RPT with dual constraints from both the model and the data. A case study in the Jiyang Depression demonstrates that the proposed dual-constrained 3D RPT delivers highly accurate and applicable predictions of shale oil reservoir properties. This approach establishes a novel strategy of RPT construction and application for complex shale reservoirs.