For the successful integration of refugees, it is essential to place refugees in a municipality that best matches their personal needs and future plans. It is therefore important to individualize the choice of location with the highest possible match to personal attributes and needs of a refugee. In this paper, we describe the development of the Match’In system, a recommender system that recommends municipalities for the integration of refugees, based on the knowledge representing an individual refugee and his or her needs. We describe the knowledge elicitation and formalization process we developed and applied in the Match’In project. A participatory and multi-stage process was used to develop the algorithm-based decision support system for the individualized recommendation of municipalities for refugees. We detail on the decision and rational of using case-based reasoning (CBR) as the reasoning approach within the Match’In system. We then describe the specific capabilities of the use of structural CBR in terms of transparency of the knowledge model, with an emphasis on the detection and prevention of algorithmic bias. We further describe the reasoning technique and the possibilities to automatically derive explanations from these to justify the recommendation of specific municipalities by the Match’In system.