New psychoactive substances (NPS-New Psychoactive Substances) are increasingly present in discussions regarding law enforcement issues and public policy. However, there are still gaps in the classification and characterization of those substances that were never identified or those already known but reported because of abusive use. To understand more about these substances, especially amphetamines, and cathinones, this work sought to deepen studies using in silico methodologies. Spectroscopic investigations were carried out using three approaches: Nuclear Magnetic Resonance (NMR), Infrared (IR), and Ultraviolet-Visible (UV-Vis). Data referring to each technique were obtained through theoretical chemistry methods. Density Functional Theory (DFT) was used to collect data both in the gas phase and in solvents. The idea was to obtain a more reliable reproduction of the experimental results. Problems related to the presumptive and confirmation tests for the substances were evaluated. Different chemometric approaches were used to verify the suitability of the simulated data to the experimental ones. All techniques provided satisfactory results for the characterization of the studied classes. The models resulting from NMR and IR evaluations were able to help in the interpretation of identification data. Besides, they can be a good source of reference standards by offering spectroscopic information. The study carried out with UV-vis indicated that, for the presumptive evaluation, there is no clear differentiation between the classes, requiring additional characterization techniques, according to international guidelines. We concluded that in silico methods can provide relevant information about NPS. These studies can be done rapidly and can be able to feed decision-making, which can be helpful forensic intelligence process.