In vitro fertilization (IVF) program patients have elevated anxiety levels. Therefore, they immediately contact fertility doctors through existing communication media to get treatment. However, fertility doctors cannot respond quickly due to high workloads. The intelligent health system that implements the Case-Based Reasoning (CBR) model is widely used to assist doctors in handling patient complaints. However, the system provides opportunities for modification so that the performance of the CBR model increases and further assists fertility doctors in handling IVF patient anxiety. This study modified the CBR model by integrating several previous research results (CCBR similarity formula, combination of CBR with Rule-Based Reasoning, the role of patient feedback, and the application of a minimum standard value of 80%). Measurement of the coefficient matrix to assess system performance using the Chris Case-Based Reasoning (CCBR) similarity formula produced an accuracy value of 52.58%, and the performance of the combination of the CBR model with the Rule-Based Reasoning model increased the accuracy value by 47.42%, so it can be stated that the CCBR model is a better intelligent system model for handling IVF patient anxiety.