Introduction An evaluation of new methods of surgery in otolaryngology is done with emphasis on four advanced surgical techniques: transoral robotic surgery (TORS), image-guided sinus surgery (IGSS), endoscopic skull base surgery, and 3D-printed implant-assisted procedures. The study evaluated a sample of 300 patients from Pakistan, ensuring that the evaluation was done in the light of these technologies vis-à-vis traditional ones. Objectives The aim of this study was to evaluate the impact of such surgical innovations in terms of quality of life (QoL), complication rates, follow-up compliance, and intra-operative parameters. In addition, this study aimed to identify predictors for postoperative complications, thereby profiling potential selection biases for using these advanced techniques in surgical interventions. Methodology A retrospective cohort analysis of 300 patients was conducted, including demographic variables, clinical events, tumor volumes, and comorbidities according to the Charlson Comorbidity Index and frailty scores. Assessment of postoperative outcome parameters included QoL, complication events, and intensive care unit (ICU) stay. A random forest model was trained to predict postoperative complications and showed an accuracy of 86.7% with an AUC-ROC of 0.91. Results The TORS and 3D-printed implant groups performed much better, showing significantly higher QoL scores (84.3 and 82.5 on average), low complication rates (9.7% and 6.8%), and high follow-up compliance (87% and 84%). They also show less blood loss and less time in ICUs. However, far fewer comorbidities and smaller tumors were found in these patients, which points toward a selection bias. Conclusion Emerging surgical innovations in otolaryngology, such as TORS and 3D-printed implants, create remarkable benefits in clinical scenarios associated with QoL and complications. However, patient selection bias creates barriers to realizing equitable access to the technologies, creating space for argumentation about evidence-based practice in clinical decision-making.