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Dental identification relies on comparing dental treatment features, odontogenic morphological features or a combination of both. Treatment features are usually the first line of assessment used. However, factors such as incomplete dental records, ongoing decline in number of dental restorations has made morphological features become more important. There is at the moment, no conclusive evidence that the human dentition is indeed unique, which is the basis in being able to use morphological features for identification. The aim of this study is to identify unique tooth dimensions on panoramic radiograph for human identification purposes. Sixty-two digital panoramic radiograph from 31 females and 31 males (age ranged from 13 to 56 years old) were collected retrospectively from a private dental clinic in Belgium. Six tooth measurements were performed on all seven mandibular left permanent teeth (excluding third molars): tooth length (TL), crown length (CL), root length (RL), crown width (CW), cervical width (CEJW) and root width (RW). 9 length-width ratios were then calculated using these measurements: CL/CW, CL/CEJW, CL/RW, RL/CW, RL/CEJW, RL/RW, TL/CW, TL/CEJW, TL/RW. Analyses for the ratios were based on log-transformed values. Intra and inter observer reliabilities for each parameter were assessed in terms of intra-class correlation (ICC), standard error of measurement (SEM) and reproducibility coefficient (RC). Sex differences in measurements/ratios per tooth position were evaluated using two-way linear models and correlations between measurements/ratios per tooth position were verified with Spearman correlations. Univariate and multivariate analyses were performed to calculate ‘potential set’ for an indication of uniqueness. Combining all measurements for tooth 31 produced the lowest potential set, which indicates the most unique tooth for identification purposes. Compared to single parameters, combining measurements or ratios substantially improve the mean potential set.