Table 1 shows all studies in the literature that considered the need for validation of FEAs. According to these studies, we established a hierarchy based on the evidence level of the validations (A to G, i.e., high to low) (Fig. 2).

Level A: validation using living humans

Level B: validation using living heterogeneous animals

Levels C and D: validation using homogenous and heterogeneous bone

Level E: validation using artificial bone materials

Level F: validation using past literature

Level G: validation using other software

FEA using model verification cannot be considered to be a validation method for entire study. Model verification should be performed to ensure accurate FEA; however, finite element models verified with clinical data such as a patient’s computed tomography findings are categorized in a low level of validation or without validation. For this reason, studies that used only model verification (some studies may called it by "model validation") were not included in our review [58,59,60,61,62].

Many recent papers [10,11,12, 14, 15, 25,26,27,28,29,30,31, 33, 35, 36, 39, 41,42,43,44,45, 47, 48, 50,51,52, 54, 55, 58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74] have described the use of FEA to evaluate the stress distribution of implant fixtures and surrounding bone, with a particular focus on different fixture lengths, shapes, connection designs, and prostheses. However, most such studies [15, 58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74] were performed without validation executed under the same conditions with the FEA. The following questions are worthy of consideration by oral scientists and clinicians: Can a finite element model really create a virtual condition simulating the biomechanical behavior of the craniomandibular system? To what extent can we predict biological activities with finite element models [9]?

The complexity of living organisms and internal biological phenomena is impossible to fully and precisely duplicate with individual-level specificity using a computer. However, we can evaluate the limitations of current technology and build a model with the highest level of evidence possible.