This study introduces an expert-guided decision-support platform developed to improve the selection of building retrofit measures for energy efficiency. The platform addresses a key gap in existing tools by combining expert input with systematic decision logic, offering a more transparent and adaptable approach to retrofit planning. Unlike simulation-based or policy-orientated systems, this platform focuses on supporting real-world decisions at the property level. It allows for both general (global) and building-specific configurations, giving users the flexibility to define and adjust decision criteria based on retrofit needs. A three-phase analytical workflow supports users via assigning expert importance, classifying assessment criteria, and deciding on a ranking method. The strategy combines data-driven and expert-based weighing methodologies, resulting in balanced and context-aware outputs. The system includes an explainable AI module that generates editable reasons for final recommendations, allowing stakeholders to better understand and discuss decisions. The platform’s efficacy was demonstrated through a case study of a mid-terrace house, showing strong potential for supporting consistent, stakeholder-informed, and auditable retrofit decisions. This work contributes a flexible and scalable solution of practical value to planners, housing authorities, and retrofit consultants.