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According to underground construction development and its high cost process, an accurate assessment and prevention of probable risks are of significant importance. Different methods have been developed to assess underground constructions. In this paper, the aim is to develop a new soft computing model to evaluate tunnel support systems. Firstly, a numerical analysis was performed using the explicit finite difference model by FLAC2D software to excavate a sequence model and support system installation. The design loads including the axial force, moment, and shear force were calculated for some important points of the support system including the crown, the middle of the bottom and the side walls. In order to analyse the stability of the support system, the section points were evaluated into 3 clusters by the artificial bee colony as a meta-heuristic algorithm and a k-means algorithm using Matlab software. The results of clustering were compared by the safety factor of the support system. The results indicated that the section points that are in cluster 1 have a lower safety factor than clusters 3 and 2, respectively. It concluded that the artificial bee colony can be reliably used in the initial assessment of tunnel support systems based on the axial force, moment, and shear force.