Undoubtedly, single-vehicle crashes remain a major concern for roadway users and highway administrators, especially in low- and middle-income developing countries, where accident death rates remain extremely high. This study investigated the temporal instability of contributing factors of driver-injury severities in single-vehicle crashes using data in Thailand, a developing country, from 2011 to 2017. The uncorrelated and correlated random parameters model, which enable a possible heterogeneity in means and variances approaches, were estimated for individual year model using two levels of driver-injury severities, namely, no/minor injury and severe/fatal injury. The models considered a wide range of factors, such as driver, roadway, vehicle, crash, environmental and temporal, and spatial characteristics. The series of likelihood ratio test and the marginal effect of significant factors were computed to explore the temporal stability of the year models and to investigate the temporal instability of the effect of each parameter estimate on the probability of driver-injury severities within given time periods, respectively. The result indicates that a substantial temporal instability exists in the model specifications and estimated parameters (temporally unstable factor included male driver, driving using exceeding speed limit, crashes on asphalt pavement, crashes on weekends, and crashes on weekend during nighttime with present of road lighting) across the time periods under study (despite insignificant in particular year models, some factors were stable but marginal effects varied across time). The findings may be used to assist and guide decision makers in policy generation for plans to mitigate driver-injury severities. Despite the unclear source of temporal instability, the finding emphasizes the importance of the temporal instability of the factors that influence the outcomes of driver-injury severities. Alternatively, ignoring temporal instability in studies on crash severity may lead to high levels of bias and inaccurate conclusions. With regard to methodologies, both random parameters with heterogeneity in means and variances and correlated random parameters with heterogeneity in means approaches are promising methods with ability to offer another layer of insight into unobserved heterogeneity in injury severities research.