Magnetic seeded filtration (MSF) is a multidimensional solid–liquid separation process capable of fractionating a multimaterial suspension based on particle size and surface properties. It relies on the selective hetero-agglomeration between nonmagnetic target and magnetic seed particles followed by a magnetic separation. Experimental investigations of multimaterial suspensions are challenging and limited. Therefore, a Monte Carlo model for the simulation of hetero-agglomeration processes is developed, validated, and compared to a discrete population balance model. The numerical investigation of both charge-based and hydrophobicity-based separation in an 11-material system, using synthetic agglomeration kernels based on real-world observations, yields results consistent with prior experimental studies and expectations: Although a multidimensional separation is indeed possible, unwanted hetero-agglomeration between target particles results in a reduced selectivity. This effect is more pronounced when separation is based on a dissimilarity rather than a similarity in the separation criterion and emphasizes the advantages of hydrophobicity-based systems. For the first time, 2D grade efficiency functions T(φ,d) are presented for MSF. However, it is shown that these functions strongly depend on the initial state of the suspension, which casts doubt on their general definition for agglomeration-based processes and underlines the importance of a simulation tool like the developed MC model.