This paper presents a data scientist’s approach to personal injury recovery. After experiencing a back strain due to improper weightlifting technique, the author leveraged their analytical skills to track and analyze factors influencing their healing process. This included generating a hypothetical dataset and building a linear regression model to explore the relationship between age and recovery time. While the initial model demonstrated limitations in accuracy, the process served as a valuable distraction from negative thoughts and allowed the author to delve into relevant research, ultimately promoting a data-driven approach to recovery.