Cocrystals have significant potential in various fields such as chemistry, material, and medicine. For instance, pharmaceutical cocrystals have the ability to address issues associated with physicochemical and biopharmaceutical properties. However, it can be challenging to find proper coformers to form cocrystals with drugs of interest. Herein, a new in silico tool called 3D substructure-molecular-interaction network-based recommendation (3D-SMINBR) has been developed to address this problem. This tool first integrated 3D molecular conformations with a weighted network-based recommendation model to prioritize potential coformers for target drugs. In cross-validation, the performance of 3D-SMINBR surpassed the 2D substructure-based predictive model SMINBR in our previous study. Additionally, the generalization capability of 3D-SMINBR was confirmed by testing on unseen cocrystal data. The practicality of this tool was further demonstrated by case studies on cocrystal screening of armillarisin A (Arm) and isoimperatorin (iIM). The obtained Arm-piperazine and iIM-salicylamide cocrystals present improved solubility and dissolution rate compared to their parent drugs. Overall, 3D-SMINBR augmented by 3D molecular conformations would be a useful network-based tool for cocrystal discovery. A free web server for 3D-SMINBR can be freely accessed at http://lmmd.ecust.edu.cn/netcorecsys/.