This paper proposes an interactive web-based Python dashboard tool for allowing any users to easily predict students at risk and help make decisions about avoiding student dropout. The user must not necessarily have the programming skills required to develop a machine-learning project. Instead, our system will allow the user to upload students¿½f information dataset, and automatically will generate the best possible prediction model and explanations. The novelty of this tool is that it integrates Automated Machine Learning (AutoML) and Explainable Arti-ficial Intelligence (XAI) techniques, especially counterfactual explanations, into the same interface to make the process more accessible. The objective is to democratize and personalize data science by allowing any stakeholder, to make predictions of student dropout from a dashboard. It provides two different interfaces: a basic interface for beginners and a more complete interface for advanced users. In this paper, we describe the use of the dashboard on a free public dataset for predicting student dropout.