Successful software project survival and progress over time is highly dependent on effectively managing the maintenance process. Estimating accurately maintenance process factors like the maintenance effort and the level of changes required for a new release is considered a crucial task for allocating resources. In this work we examine the maintenance process factors of JavaScript applications, which at the moment are understudied despite the need of language specific maintenance models. Furthermore we propose two maintenance indices for estimating the changes and the effort required for maintaining JavaScript applications by considering a variety of maintenance drivers. We evaluated the proposed indices through a case study on 5,788 releases coming from 60 popular JavaScript applications. The results show that project activity factors (i.e., number of open bugs and number of corrective maintenance activities) are important maintenance drivers. The proposed indices are evaluated in terms of predictive and discriminative power and both achieve high accuracy.