This article created and tested multiple predictive models for cancer survivors’ future quality of life (QoL) and overall health status, measured by physical, mental, social, and spiritual health. The authors found that basic demographic information including social and clinical factors were highly predictive of the QoL of the cancer survivors (AUPRC =0.80). Most influentially, they found that self-management strategies (SAT) scores were even more predictive of the QoL of the cancer survivors (AUPRC= 0.96). Results showed that a simple model linking the SAT factors to QoL can be employed to accurately address the QoL of cancer survivors in clinical settings. Specifically, the activity coping strategy of the SAT-Implementation (SAT-I), a strategy used to implement necessary health and treatment behaviors, was the most important predictive factor in the QoL of cancer survivors, indicating that SAT-Is may influence health behaviors that can influence QoL. In linking overall health status to QoL, the cancer survivors' mental (AUROC=0.71), social (AUROC=0.77), and spiritual health (AUROC=0.75) statuses demonstrated good predictive results, though compared to the SAT predictive model, this health status model predicted a lower QoL than in actuality of the cancer survivors. That being said, the complex and subjective nature of QoL indicates that creating a customized SAT plan given a patient’s needs and circumstances may lead to the best QoL outcome. The XGBoost model finalized in the study demonstrated a strong predictive ability (AUC=0.80, Brier Score=0.07). Using SHAP, a new XAI technology, the study was also able to provide participants with individualized healthcare services following their questionnaire responses.