Logistic regression is a popular tool used to build and evaluate binary choice models. It has been applied in a variety of situations and contexts involving dichotomous choice. In the current paper, we apply it to explain and predict the individual choice of adopting online learning through a Massive Online Open Course (MOOC), a specific artefact in the domain of online, open learning. The MOOC holds promise for a developing country like India to scale quality education to keep up with an overwhelming demand of its large population. Hence the importance of the choice to enter MOOCs in the Indian context cannot be overemphasized. Factors possibly driving MOOC adoption were selected after an extensive literature study and a binary logistic regression model was applied to analyze their influence using data from a primary survey. A variety of different subsets of possible explanatory variables under consideration were experimented with. Due diligence was exercised with respect to model selection and evaluation and a 'best' model was identified and discussed. Among other things, our proposed model suggested that a respondent's online communicative efficacy was the strongest predictor of MOOC usage and similarly their preference for self-directed learning. In terms of practice and policy, the results of this study underline the need for strategies for enhancing digital literacy, online efficacy, self-directed learning and e-readiness of the prospective higher education aspirants in order to help with wider MOOC outreach and adoption in a developing country like India.