Consumption of alcohol is identified as the important reason to influence the individual’s health. Unnecessary use of these type of drugs develops challenging unsystematic behaviours. These behaviours may be like addiction. It also primes to early death, sickness, and generate significant imbalance in society. To the entire globe the drug consumption and addiction bring severalserious issues. The civil libertarians consider the drug abuse is an individual choice. But the issue here is that the side effects of drug abuse such as early death or decreased individual working also affects the persons who were not a drug user. Currently, the treatment strategies to the unsystematic behaviours often observed to be fixed with standardprocedures. Theindividual personalitybehaviourist to be considered as important feature in locating effective treatment strategies. The proposed work tries to explore the drug usage vulnerability risk prediction through collection of individual personality trails depending on their drug consumption details. Depending on the self-extracted data collected from 1885 individuals three of the NN models were built. These three NN models apply the 10-Fold cross validation and 30-70 Hold-Out validation methods to provide the reliability of the prediction results. Among the three methods the RNN Hold-Out method achieve 99.11% as best accuracy result.

Drug Consumption, Personality Trails, Neural Network, FFNN, CFNN, PNN.