The liver is the largest gland and vital organ in the human body that plays an important role in detoxification, metabolism, and the immune system. Disruption of liver function can cause various serious diseases, including hepatitis, liver cancer, and cirrhosis. Liver cirrhosis, which is characterized by liver tissue damage and scarring, has a significant impact on global health, with around 1.03 million deaths each year. Reports from Indonesian government general hospitals show that around 3.5% of patients treated in internal medicine wards suffer from liver cirrhosis. The majority of sufferers of this disease are women aged 50 years and over, with a ratio of women to men of 8:1. This study uses secondary data obtained from the UC Irvine Machine Learning Repository in the form of a set of data on predicting the survival of Primary Biliary Cirrhosis (PBC) patients. The data was collected from a study conducted at the Mayo Clinic with 312 patients. In this study, the method used to estimate the survival chances of PBC patients was nonparametric censored type III with the Kaplan Meier method. Based on the results of the analysis, it was obtained that the results of the product limit estimator or Kaplan-Meier calculation and the survival plot of PBC patients who survived for 41 days had a greater chance of survival than PBC patients who survived for 4556 days. In addition, based on the analysis, it was shown that female PBC patients had a higher average survival estimate than male PBC patients. This is inseparable from the influence of various factors. Therefore, this study is expected to help develop more effective treatment strategies and provide more accurate predictions regarding the prognosis of PBC patients.