This contribution presents a numerical modeling approach developed for simulating the dynamic response of 3D-printed unreinforced-masonry-like (URM-like) structures under earthquake loading, as part of a blind prediction contest organized by the Pacific Earthquake Engineering Research Center (PEER), ETH Zürich and NTU Athens. Masonry is a popular construction material around the world but highly vulnerable to lateral loads, with out-of-plane (OOP) collapse of walls being a critical failure mode. Understanding the OOP response of URM requires not only physical tests, but also robust approaches for numerical investigation. The PEER competition offered an opportunity to validate numerical models against shake table tests conducted in ETH Zürich. 29 identical 1:15-scaled, sand-based 3D-printed URM-like substructures, each consisting of a longitudinal wall intersected by two transverse walls, were subjected to unique ground motions derived from historical earthquakes, in the OOP direction of the longitudinal walls. The high-fidelity 3D modeling approach developed by the authors for the dynamic analysis of URM walls was used to participate in the contest and simulate the 29 tests. The approach was modified to suit the specific geometry and material characteristics of the tested specimens. Firstly, unlike traditional unit-based construction, the specimens were printed as single "continuum" bodies with cuts to replicate joints. This needed to be translated into the discrete framework of the modeling approach, wherein individual blocks connected via zero-thickness interfaces were used. Secondly, scaling effects on Dynamic behavior due to the miniature experimental specimens required special consideration. The resulting numerical approach simulated the response of 29 specimens with high accuracy in replicating collapse probability, maximum displacements, and failure mechanisms observed during the experiments, achieving the best outcomes among participants and winning the contest. Such a reliable approach enables broader case studies and supports adaptation to innovative URM construction methods like 3D printing.