||Twitter is a very important source for obtaining information, especially during events such as natural disasters. Users can spread information in Twitter either by crafting new posts, which are called “tweets,” or by using retweet mechanism to re-post the previously created tweets. During natural disasters, identifying how likely a tweet is to be highly retweeted is very important since it can help promote the spread of good information in a network such as Twitter, as well as it can help stop the spread of misinformation, when corroborated with approaches that identify trustworthy information or misinformation, respectively. In this paper, we present an analysis on retweeted tweets to determine several aspects affecting retweetability. We then extract features from tweets’ content and user account information and perform experiments to develop models that automatically predict the retweetability of a tweet in the context of the Hurricane Sandy.