Objective: In this study, a novel voxel-by-voxel mixing method is presented, according to which two filaments of different material are combined during the 3D printing process. Approach: In our approach, two types of filaments were used for the replication of soft-tissues, a polylactic acid (PLA) filament and a polypropylene (PP) filament. A custom-made software was used, while a series of breast patient CT scan images were directly associated to the 3D printing process. Each phantom´s layer was printed twice, once with the PLA filament and a second time with the PP filament. For each material, the filament extrusion rate was controlled voxel-by-voxel and was based on the HU of the imported CT images. The phantom was scanned at clinical CT, breast tomosynthesis and Micro CT facilities, as the major processing was performed on data from the CT. A side by side comparison between patient´s and phantom´s CT slices by means of profile and histogram comparison was accomplished. Further, in case of profile comparison, the Pearson´s coefficients were calculated. Main results: The visual assessment of the distribution of the glandular tissue in the CT slices of the printed breast anatomy showed high degree of radiological similarity to the corresponding patient´s glandular distribution. The profile plots´ comparison showed that the Hounsfield Units (HU) of the replicated and original patient soft tissues match adequately. In overall, the Pearson´s coefficients were above 0.91, suggesting a close match of the CT images of the phantom with those of the patient. The overall HU were close in terms of HU ranges. The HU mean, median and standard deviation of the original and the phantom CT slices were -149, -167, ±65, and -121, -130, ±91, respectively. Significance: The results suggest that the proposed methodology is appropriate for manufacturing of anthropomorphic soft tissue phantoms for x-ray imaging and dosimetry purposes, since it may offer an accurate replication of these tissues.