Interval neutrosophic numbers (INNs) offer a more advanced framework for representing fuzzy information than neutrosophic and intuitionistic fuzzy numbers. However, existing distance measures for INNs have limitations. To address these, this chapter introduces a novel triangular divergence-based distance measure, which is demonstrated to be superior through an illustrative example. The “Compromise Ranking of Alternatives from Distance to Ideal Solution” (CRADIS) method is enhanced by integrating this new distance measure, extending its applicability to the INN context. A new multi-attribute group decision-making (MAGDM) method is developed using the modified CRADIS method with unknown weights. The R-method is used to determine expert weights, and the rank-sum method assesses criteria weights. This MAGDM method is applied to a green supplier selection problem, identifying the first supplier as the best choice. A comprehensive sensitivity analysis confirms the method’s stability, while comparative analysis with other methods validates its practical applicability and improved performance. The findings underscore the method’s effectiveness in decision-making within the INN framework.