An Agile development team estimates the effort of a work item to plan a sprint (i.e., an iteration in Scrum). Hence, reliable effort estimation would help the team create a reliable sprint plan. Prior studies proposed automated approaches to help the team to estimate the effort accurately. However, the effort estimated by the previously proposed approaches may become inaccurate when the related information is changed. Especially when the estimated effort is changed after the sprint has been planned, the sprint plan may be invalidated and the team might waste their time and effort spent in planning. This thesis aims to help the Agile development team improve the stability of effort estimation (in the Story Points unit) while aligning with the just-in-time practice of Agile. Hence, we first conduct empirical studies using mixed-methods approaches to investigate the potential impact of instability of Story Points. To help an Agile team to achieve reliable effort estimation with optimal effort, we will develop approaches to predict the future Story Points changes and the future information changes to help the team cope with uncertainty when finalizing the sprint plan.