Purpose: To evaluate the correspondence between output from a new artificial intelligence tool (AIT) and clinician evaluation regarding the immediate loading suitability of dental implants based on insertion torque curves recorded during implant placement in an in vitro test. The secondary aim was to analyze peak insertion torque (PIT) and variable torque work (VTW) values of the implants. Materials and Methods: The study was performed with four different densities of artificial bone blocks of solid rigid polyurethane without a cortical layer. Five types of implants with different macrogeometries were used. A total of 140 implants (7 implants of each type in the four polyurethane blocks) were inserted. Immediately after implant placement, the insertion torque curves were classified by the operator as suitable (S) or nonsuitable (NS) for immediate loading. The same curves were then analyzed by the new AIT, which classified them as belonging to the “YES” or “NO” class. For each implant, PIT and VTW values were also recorded. Results: The correspondence between clinician and AIT evaluation was 99.3%, with only one false negative reported by the algorithm analysis. The AIT was found to have a sensitivity of 98.95%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 97.8%. Mean PIT of the whole sample was 34.19 ± 19.43 Ncm, while mean VTW was 2,266.89 ± 1,993.73 Ncm. Statistically significant differences were found between implant systems in the whole sample and according to density of the polyurethane block. Conclusions: The AIT showed a high level of accuracy in the prediction of immediate loading suitability of dental implants based on the provided insertion torque curves. All the implants used in the in vitro test achieved good levels of primary stability, except when inserted in the least-dense polyurethane block. Clinical studies conducted with larger samples and more clinicians are necessary to confirm these results.