The present study aims to interpret management student's motivation to adopt m-learning and assesses the determinates impacting the behavioral intent of m-learning adoption. A comprehensive research archetype is proposed by integrating two prominent theoretical models, namely UTAUT and UGT. The research model is tested using multi-analytic structural equation modeling (SEM) and advanced neural network (ANN) approach. The quantitative data was gathered and measured from 220 management students. The study outcomes reported that affective need, performance expectancy, effort expectancy, social influence and facilitating conditions positively impacted the student's intent to use m-learning, whereas cognitive need was found to be insignificant in predicting and explicating the m-learning adoption. The results of sensitivity analysis revealed that effort expectancy showed the highest normalized importance (100%) followed by performance expectancy (97.2%) in explicating the m-learning adoption. The research archetype was able to elucidate 66% of variance in student's intent towards m-learning adoption. In addition to that, Cohen's f-square statistic resulted in effect size as 0.771 indicating that the study findings were relevant and substantial with the empirical data collected. Conclusively, the theoretic and managerial implications are described for the proposed model.