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The aim of judgment aggregation is to make collective decisions based on the judgments of individual agents. Some rationality con-ditions governing the expected behavior of the aggregation function must be considered. However, impossibility theorems show that de-signing an aggregation function satisfying all desirable properties is not feasible. While some rationality conditions are very natu-ral ones, other ones are more disputable. We show that this is the case of the systematicity condition that prevents from electing is-sues with more votes than others. Instead, a neutrality condition and a swap optimality condition are promoted. Swap optimality ensures that among two possible results, the one with the best sup-port (number of votes) is chosen. We introduce a new family of judgment aggregation methods based on the support (number of votes) that each issue receives