1. A computer-implemented method performed by a processor, the method comprising: obtaining a training dataset, the training dataset comprises a sample of data-points, wherein with respect to each data-point a label is provided; training a reliability classifier tool using the training dataset and predictions made with respect to data-points of the training dataset made by a classifier tool in response to a training session, wherein the training session comprises training the classifier tool with respect to a portion of the training dataset; obtaining a prediction of a label for a dataset made by the classifier tool, wherein the classifier tool is aimed at predicting the label based on a classification model and in view of a set of features defining the dataset; obtaining a reliability prediction of a reliability label for the prediction based on the reliability classifier tool, wherein the reliability classifier tool is aimed at predicting the reliability label based on the classification model and in view of a second set of features that were not utilized by the classifier tool; and outputting, at a same stage, to a user the label prediction and the reliability label which indicates a reliability of the label prediction.