Statistical Energy Analysis (SEA) is a numerical method designed to predict vibroacoustic energy flow in complex systems. Loss factors are the main parameters describing the SEA model. Loss factors are positive real numbers and can be predicted theoretically or measured. Unfortunately, experimentally determined loss factors may be negative due to the inversion of the error-sensitive matrix. One recently proposed method utilizes Monte Carlo Filtering (MCF) to correct negative loss factors. In this paper, we introduce and validate a simple quality-control tool that allows checking if performed negative loss factor correction delivered physically meaningful results. To achieve this, we propose to utilize the Total Loss Factor criterion. This approach requires additional calculations in which only a single subsystem is considered, and all junctions are ignored. Experiments were performed on nine systems comprising junctions commonly used in the industry. MCF was then used to correct negative loss factors in some frequency bands. We have shown that a poorly generated Monte Carlo sample can lead to results that do not fulfill the required criterion, even though negative loss factors were no longer present. Narrowing the search area during sample generation was crucial to obtain quality results that met the TLF criterion.