Closing a question on a community question answering forum such as Stack Overflow is a highly divisive event. On one hand, moderation is of crucial importance in maintaining the content quality indispensable for the future sustainability of the site. On the other hand, details about the closing reason might frequently appear blurred to the user, which leads to debates and occasional negative behavior in answers or comments. With the aim of helping the users compose good quality questions, we introduce a set of classifiers for the categorization of Stack Overflow posts prior to their actual submission. Our binary classifier is capable of predicting whether a question will be closed after posting with an accuracy of 71.87%. Additionally, in this study we propose the first multiclass classifier to estimate the exact reason of closing a question to an accuracy of 48.55%. Both classifiers are based on Gated Recurrent Units and trained solely on the pre-submission textual information of Stack Overflow posts.