In this paper, the unfeasibility of producing "objective" probabilistic climate change scenarios is discussed. Realizing that the knowledge of "true" probabilities of the different scenarios and temperature changes is unachievable, the objective must be to find the probabilities that are the most consistent with what our state of knowledge and expert judgment are. Therefore, subjective information plays, and should play, a crucial role. A new methodology, based on the Principle of Maximum Entropy, is proposed for constructing probabilistic climate change scenarios when only partial information is available. The objective is to produce relevant information for decision-making according to different agents' judgment and subjective beliefs. These estimates have desirable properties such as: they are the least biased estimate possible on the available information; maximize the uncertainty (entropy) subject to the partial information that is given; The maximum entropy distribution assigns a positive probability to every event that is not excluded by the given information; no possibility is ignored. The probabilities obtained in this manner are the best predictions possible with the state of knowledge and subjective information that is available. This methodology allows distinguishing between reckless and cautious positions regarding the climate change threat.