The Deep Soil Mixing (DSM) material is a cementitious composite consisting of a well-mixed soil/cement matrix and may contain unmixed soil inclusions and possibly gravel. To obtain a 3D reconstruction of a DSM specimen structure, a destructive method was investigated, as an alternative to X-Ray Computed Tomography scans. The proposed method is based on image analysis and photographs of few millimeters thickness slices of a specimen. A detailed morphological description of inclusions, including volume fraction, shape, size distribution and spatial arrangement using common image analysis and CAD softwares preceded the validation of the 3D destructive method by the non-destructive X-ray CT based on 3 criteria (volume fraction, size distribution and shadow zone area). Compared to 1D and 2D basic methods found in the literature, the 3D developed method prevented biases linked to the external surface estimation of inclusions’ volume fraction. Next, to improve the experimental procedure, an extended methodology was established for estimating the inclusions volume fractions. Such method relies on a database of 3D reconstructed inclusion shapes and on the optimization of the sawing thickness. The aim consisted in the obtaining of unbiased estimates of the volume fractions with fewer cuts, between 4 and 18 instead of 50–60, which made such method as a low-cost, practical and accurate procedure. Finally, the 3D mesh generated by the 3D destructive method was used in numerical approach to propose, as an example, a successful hydromechanical numerical simulation of the DSM material response. Furthermore, a machine learning framework using the 2D slices of specimens produced during the application of the 3D destructive method, was proposed to generate various realistic 3D shapes instead of the usual spherical shape for inclusions, which will allow testing high number of meso-structures in numerical simulation.