Objectives: 1) Study the predominant palatal rugae characteristics in Angles classes of malocclusions. 2) Statistically relate the major palatal rugae characteristics with Angles classes of malocclusions and thereby study the probability of employing it in forecasting malocclusions. Materials and Methods: The data for classifying malocclusion was obtained from the patients’ clinical records. Study casts of the palate of 100 healthy orthodontic patients were included as Class 1, Class 2 and Class 3 respectively. Palatal rugae characteristics for all groups were recorded and Class 2 was compared with Classes 2, and 3 according to angles classification and analyzed. Distribution of 100 study casts for the study- 34 Class 1; 34 Class 2 and 32 Class 3. Inclusion Criteria: 1) The casts were categorized into class 1, 2 and 3 based on the ANB angle of 0-4 degrees for class 1, more than 4 degrees for class 2 and less than 0 degrees for class 3. 2) No previous orthodontics treatment. 3) No anomalies. Exclusion Criteria: 1) Study casts of inferior quality. 2) Records of any patient having history of previous anomalies affecting the maxilla rugae. Statistics: Predominant palatal rugae data of groups was entered in SPSS (version 10.0) software and statistically analyzed using ANOVA test to assess the differences between Class 1, 2 and 3 malocclusions study casts for the palatal rugae. Palatal rugae size (length) and number analysis shall be using Krukas-wallis test. The Pattern (Shape) and orientation (Position) of the palatal rugae shall be assessed using chi-square test. Results: Wavy and complex rugae were prevalent in Class 1 and 3 malocclusions and showed statistically significant difference between Class 1, 2 and 3 malocclusions (p=0.00, 0.014 and 0.016 respectively). The wavy pattern was higher in Class 1 and horizontal and complex higher in Class 3. Conclusions: Predominant palatal rugae can be considered on vaticination of malocclusions, still, clinical correlation is must. Further studies could be accepted to develop digital styles to identify predominant palatal rugae and prognosticate malocclusion.