The buildings sector must undergo a rapid and meaningful transformation towards achieving net-zero targets. A critical part of this transformation is upgrading existing buildings through energy retrofitting. Decision-making in retrofitting projects is often done by intuition, leading to sub-optimal outcomes that miss energy, carbon, and cost targets. Trade-offs between energy, carbon, and cost are rarely addressed systematically. While previous research has emphasized and shown the importance of quantifying the trade-offs and selecting the optimized retrofit measures using Multi-Criteria Decision-Making (MCDM), industry adoption remains limited. This is largely because MCDM is a complex task, and the collaboration and information required are either unavailable or too fragmented within the industry. Existing studies fail to sufficiently address MCDM in energy retrofitting from a practical perspective and tackle these issues. This research addresses this gap by developing information requirements for MCDM in energy retrofitting, particularly for energy analysis, life cycle analysis (carbon) and life cycle cost analysis (cost). The information requirements respond to what information is needed, how much is required, and for which purpose. The research was conducted in direct consultation with 20 industry practitioners representing seven different disciplines linked to energy retrofitting: ESD consultants, design specialists, façade specialists, HVAC engineers, quantity surveyors, BIM specialists, and asset managers. A Delphi approach consisting of three rounds was adopted for this study until a final set of Energy Retrofitting Information Requirements (ERIR) for MCDM was developed. The ERIR provides clear information requirements and maps the retrofit process, bridging the gap between disciplines by identifying the responsible stakeholders. This helps resolve the information and collaboration issues needed for such complex decision-making in the industry. It supports the implementation of MCDM and potentially leads to more robust and optimum decision-making in energy retrofitting projects.