It was introduced in dentistry to be used in innovative research and development in addition to facilitating the decision in complicated cases and ensure high patient care quality. In the field of Orthodontics in specific, many studies previously mentioned the idea of artificial intelligence showing very promising results and high degree of reliability. It was used in different domains in orthodontics like diagnosis, treatment planning, evaluation of treatment outcome

In this study, the aim is to access the efficiency of the new decision support system in determining whether the decision is extraction or non-extraction and the anchorage plan required for each case. This was performed in the past in many countries and those studies are published

Inclusion Criteria:

1. Cases with well finished orthodontic treatment.
2. Cases with history of crowding more than 10 mm and requiring extraction.
3. Cases with no severe skeletal discrepancy.
4. Well documented cases with both pre-operative and post-operative records.
5. Patients with a full set of permanent teeth erupted

Exclusion Criteria:

1. Improperly finished orthodontic cases.
2. Cases with mild crowding managed by treatment options other than extraction.
3. Growing patients or showing any residual growth remaining in cephalometric analysis
4. Cases with severe skeletal discrepancy.
5. Poorly documented cases.
6. Patients not sticking to anchorage plan

Recruiting well finished cases having history of crowding from Kasr el Ainy with no severe skeletal discrepancy, cases should be well documented. The precise and complete documentation of the patients in terms of the presence of:

1. Preoperative and postoperative x-rays.
2. Good quality preoperative and postoperative photographs.
3. Preoperative and postoperative study models.
4. Detailed documentation of the treatment sequence and mechanics. If there were incomplete data provided in the patient's file; the patient will then be excluded from the study.