Background In forensic odontology, age estimation is vital for identification, legal, and investigative purposes. Teeth, resistant to external factors, serve as reliable indicators of biological maturity. The present study aims to assess the accuracy and reliability of age estimation by comparing pulp-to-enamel volume ratios from 3D imaging with the Tooth Coronal Index (TCI) method using panoramic radiographs. Methodology This prospective study analyzed 620 radiographs from participants aged 16-65 years, categorized into five age groups. Using random sampling, 320 images each were evaluated using the following two methods: TCI measured from panoramic radiographs and pulp-to-enamel volume ratio using cone-beam computed tomography (CBCT) and 3D Slicer software. TCI was calculated using crown and pulp cavity heights from maxillary first (MX1) and second molars (MX2) and mandibular first (MND1) and second (MND2) molars. CBCT scans were processed in DICOM format for 3D segmentation and analysis of pulp volume (PV) and enamel volume (EV). Statistical analyses were performed using SPSS version 26.0 (IBM Corp., Armonk, NY, USA), employing t-tests, analysis of variance, and regression analysis. A p-value <0.05 was considered statistically significant. Results Among 320 teeth analyzed, TCI showed a statistically significant correlation with age only for MX2 (p < 0.05). The standard error of estimate for TCI-based age prediction was 14.57 years, with poor regression equations (R² ≈ 0). PV/EV analysis demonstrated a strong correlation with age (R² > 0.8), with a standard error of 4.34 years. Linear regression equations derived for PV/EV provided reliable age predictions. MX1, MX2, and MND2 PV/EV showed a significant positive correlation with age (p < 0.01), with R² nearing 1 for individual predictors. The youngest subject was 16 years old, and the eldest was 64 years old. Conclusions Considering certain limitations, this study concluded that 3D imaging, particularly utilizing maxillary and mandibular molars, demonstrates greater accuracy in age estimation compared to 2D imaging and shows significant potential for forensic applications.