Although arteriovenous fistula is the preferred vascular access method, it has challenges in three phases of planning, maturation, and maintenance. We looked at the root of fistula challenges in the maintenance phase and found traces of inflammation. Accordingly, we investigated the role of systemic inflammation in this phase to understand its effects on post-maturation function and extract knowledge to help extend fistula longevity. Previous studies on longevity of fistula have focused entirely on statistical tests, and since they put limitations on data, we also used a data mining framework for data analysis. For prediction, we used Decision Tree, Random Forest, and Support Vector Machines, and for inferential analysis, we used Wilcoxon and Chi-squared tests. We analyzed the archived data of 119 hemodialysis patients. In these data, independent variables were serum inflammatory markers, serum metabolic values, anti-inflammatory drugs, and demographic characteristics, and the dependent variable was fistula longevity separated in classes of equal to or greater than four and less than four years. Both predictive and inferential approaches have shown that serum inflammatory markers had no significant involvement in fistula longevity, but some anti-inflammatory drugs were effective. The results have shown that blood tests and drug variables, alone or together, could predict longevity class by 100% accuracy. This prediction can help surgeons make better decisions in selecting patients for fistula creation. Also, the extracted knowledge can provide guidelines for post-maturation disorders.