In manufacturing industries, reliability analysis of cutting tools is of paramount importance,as their frequent failures may result in enhanced downtime of production lines,leading to reduced throughput, enhanced process cycle times,and low profits. There are numerous factors that govern the desired operations of cutting tools,e.g.,tool cutting speed,feed, depth of cut,and many others. Existing literature on cutting tools'reliability estimation emphasizesmainly three variables,as mentioned earlierwhileneglecting other important factors. Including a greater number of factors in the process of estimating reliability increases the number of covariates,hence rendering the data acquisition costlier and estimation models highly complex.This work initially utilizesAnalytical Hierarchy Process (AHP) to assessthe importance of various factors that are responsible forthe cutting tool's performance,followed bythe reliabilityestimation of the cutting toolsusing proportional hazards model (PHM) consideringthe four"critical to reliability" factors as obtained through AHPas covariates.Theproposed methodalsohelps indeterminingthe relationship of these sub-factors with the hazard rate and reliability of the cutting tools.Experimental results arethenused to verify the model's predictions through response surface methodology(RSM)and Weibull fit.Furthermore, the paperalso presents a proposed techniqueto estimate the required number of cutting tools for onemachine per day and the number of job completions that can bean essentialtakeaway for various industries.Thus, this research paper proposes an integrated AHP-RSM-PHM based approach for a comprehensive reliability analysis of cutting tools.