Background: Systemic Lupus Erythematosus (SLE) is a multi-systemic autoimmune disease linked to significant morbidity and mortality. Multiple challenges are found in the diagnosis of SLE, due to overlap with other autoimmune pathologies, in addition to wide variation in disease manifestation across racial and ethnic groups. Thus diagnosis can be delayed by several months or years, which carries the risk of progressive organ damage. Currently, the mortality rate of SLE in Oman is estimated at 5%. Once diagnosed, physicians set up a treatment plan to control symptoms as there is currently no cure. Improving early diagnosis of SLE will lead to lower flare rates and better healthcare outcomes. Despite previous research indicating several characteristics that are unique to the Arab region, publications that are unique to Oman population are scarce. Aims: (a) Design an early-prediction explainable framework to detect the presence or absence of SLE, (b) Identify the minimum set of clinical features that achieves the highest prediction, and (c) leverage interpretability method to explain the predictions for physicians. Methods: From a dataset of randomly selected 219 patients with SLE or control rheumatologic diseases, clinical and demographic features were analyzed to focus on early stages of the disease. Several feature selection algorithms and classifiers were applied to identify the best performing combination. SHAP explainer algorithm was then applied on the best achieving model to justify individual predictions and rank features based on contribution. Results: A combination of Recursive Feature Elimination (RFE) and CatBoost achieved the best performance, an AUC score of 0.95 and an F1-score of 0.89 with only 13 clinical features. Four clinical features (alopecia, renal, ACL, and hemolytic vii anemia) along with the patient's age were shown to have the greatest contribution to the prediction by SHAP algorithm. Our system was able to pick up on patterns of specific features and age groups that are associated with the disease. This will help physicians to further investigate SLE presence within a patient at early stages where symptoms are not yet adverse. Moreover, three of the four critical features were found to persist across other Arab cohorts. Additional validation by experts shows the potential of the generalizing model to other Arab ethnicities as well.