In this study, computational fluid dynamics was used as a powerful tool to study 3D printing and give industrially relevant information in terms of how easy or difficult a material of interest can be successfully printed. Gels of selected grains (black rice, job's tear seeds, mung bean, brown rice and buckwheat) were tested as potential 3D printing materials. Simulation was conducted by employing Bird-Carreau model, which yielded good fitting on the gels with shear-thinning characteristics. The simulated required piston pressure for printing differently tested gels was the highest for mung bean gel and reduced in descending order for gels from brown rice, buckwheat, black rice and job's tear seeds. These results are consistent with those of simulated minimum flow stress and those from printing experiments, confirming that simulated piston pressure could be used to evaluate and predict the ease of 3D printing a material.