The swing weight technique (SWT) is an approach for determining weighting factors indirectly through systematic comparison of attributes against the one deemed to be the most important. SWT consists of two general activities: (1) rank order attributes according to the relative importance of incremental changes in attribute values considering the full range of possibilities; and (2) select either the least or most important attribute as a reference point and assess how much more or less important the other attributes are with respect to the reference point. The purpose of this chapter is twofold. First, a new procedure to elicit, from a decision-maker, information regarding additive value weights (i.e., swing weights) is introduced. The procedure is a hybrid of the “balance-beam” method (BBM) and a dynamic “binary-like” interrogation (where the ith inquiry depends upon the answer to the (j - 1)st inquiry). Second, the maximum entropy methodology was used to demonstrate how to construct a set of additive value weights based solely on the elicited information.