Healthcare Recommender Systems have emerged as powerful instruments in the domain of healthcare, offering personalized and evidence-based recommendations to patients, clinicians, and healthcare providers. This chapter provides an in-depth exploration of the various applications of healthcare recommender techniques and their transformative impact on the healthcare landscape. By leveraging machine learning systems, big data analytics, and patient-specific information, these schemes exhibit potential in improving patient outcomes, enhancing clinical decision-making, and optimizing healthcare resource allocation. The chapter begins with an overview of the fundamental principles and methodologies underlying HRSs. It delves into the procedure of information gathering and preprocessing, highlighting the challenges and considerations specific to healthcare data, such as privacy and security concerns. Moreover, it discusses the significance of collaborative filtering, content-based filtering, and hybrid techniques, which serve as the backbone of these recommendation engines. An area where HRS have exhibited remarkable potential is in patient treatment recommendations. The chapter delves into the usage of such techniques to suggest personalized treatment plans based on patients’ medical histories, genetic profiles, and lifestyle factors. Additionally, it explores their role in promoting preventive healthcare measures and lifestyle modifications to decrease the danger of chronic illnesses. Furthermore, the chapter highlights the impact of HRS on clinical decision support. It illustrates how these systems assist healthcare professionals in diagnosing diseases, predicting patient outcomes, and selecting optimal treatment options. By drawing on a vast pool of medical knowledge and up-to-date research, these systems have demonstrated the ability to augment the expertise of clinicians and improve overall healthcare quality. Beyond patient care, the chapter addresses the significance of HRSs in healthcare resource management. These systems aid in streamlining hospital operations by optimizing patient scheduling, bed allocation, and medication inventory management, thus reducing costs and enhancing healthcare service efficiency. However, while the potential benefits of HRS are immense, the chapter also acknowledges the challenges and potential pitfalls in their implementation. Ethical concerns, such as algorithmic biases and transparency in decision-making, are discussed, along with the need for rigorous validation and continuous improvement. Finally, this chapter emphasizes the crucial role of healthcare recommender approaches in revolutionizing healthcare delivery. By facilitating personalized and evidence-based recommendations, these methods have the ability to transform the patient experience, elevate clinical practices, and ultimately contribute to the advancement of healthcare as a whole.