This is research aiming to improve the mode of sentence guideline by using the case-based reasoning model. The reason behind this research is to enhance consistency and equity in a fair manner with regard to judicial sentencing. Case-Based Reasoning is an AI technology that draws on the case database of the past to make informed decisions about new cases, making it highly suitable for judicial applications, since similar cases can guide sentencing options. The Case Based Reasoning model (CBR) will analyze the case attributes of relevance, prior legal precedents, and contextual elements-all in an effort to provide a tool that shall assist judges in handing down more equitable and uniform sentences. The CBR will incorporate a structured four-stage approach; case retrieval, case adaptation, case validation, and case optimization. The model will analyze key attributes of the case, including demographics of the defendants, severity of the crime, mitigating and aggravating factors, judicial reasoning in prior cases, and more attributes.