Despite the achievements in the field of instrumental methods of pollutant analysis, human error (HE) is still a significant issue affecting the quality of data obtained during environmental analysis and should be taken into account for quality risk management in the laboratory and field. Numerous scenarios that depend on the performance shaping factor (PSF) can lead to HE in the chemical analysis of environmental pollutants. Considering this, we applied, for the first time, the Success likelihood index method (SLIM) for the identification and quantification of HE in the analysis of polluting substances. As a case study, a spectrophotometric determination of ammonia concentration in water was examined. By applying SLIM, the impact of PSFs, such as procedure, experience, training, time, communication, and teamwork, on the occurrence of HE for specific activities was assessed by experts. It is estimated that “taking an unrepresentative sample” is the error with the highest probability of occurrence. The obtained results indicate that experience and training, followed by procedures and time, are PSFs that contribute to the greatest extent to the reduction of errors during the analysis of polluting substances. Considering the above-mentioned, the appropriate corrective measures that would lead to a reduction of HE in the analysis of pollutants are proposed.