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Backgrounds: Ovarian cancer is the 8th deadliest common cancer in women around the world. Almost all ovarian cancer patients would experience chemoresistance, recurrence, and poor prognosis after cytoreductive surgery and platinum-based chemotherapy. Chemoresistant cancer cells have characteristic expressions of cancer stem cell proteins (CSCs) CD44 + /CD24 - , RAD6 and DDB2. The increased expression of CD44 + /CD24 - , RAD6, and decreased DDB2 are believed to be associated with chemoresistance, recurrence, and poor prognosis of the disease. Thus, this study's objective is to analyze the correlation between the expression of CD44 + /CD24 - , RAD6 and DDB2 with ovarian cancer chemoresistance., Materials and Methods: This study was conducted with a prospective cohort of 64 patients who is divided into two groups (32 patients in each group) at the Obstetrics-gynecology and pathology department of Cipto Mangunkusumo, Tarakan, Dharmais, and Fatmawati Hospital. All suspected ovarian cancer patients underwent cytoreductive debulking and histopathological examination. Chemotherapy was given for six series followed by six months of observation. After the observation, we determined the therapy's response with the RECIST Criteria (Response Criteria in Solid Tumors) and then classified the results into chemoresistant or chemosensitive groups. Flow cytometry blood tests were then performed to examine the expression of CD44 + /CD24 - , RAD6 and DDB2., Results: There was a significant relationship between increased levels of CD44 + /CD24 -, and RAD6 (p < 0.05) levels with the chemoresistance of ovarian cancer. The logistic regression test showed that the CD44 + /CD24 - was better marker., Conclusions: These results indicate that CD44 + /CD24 and RAD6 expressions are significantly associated with ovarian cancer chemoresistance, and CD44 + /CD24 - is the better marker to predict ovarian cancer chemoresistance., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)