Intensive agricultural practices with excessive use of chemical fertiliser have led to the deterioration of soil fertility where soil losses its ability to sustain a consistent crop system with high yield. Compost is a potential substitution to chemical fertiliser. As a biological additive, compost can improve soil quality and crop productivity, controlling plant diseases and reduce nutrient loss and water pollution. However, the effect of compost application to enhance the quality of the soil may be inconsistent due to the slow release nature of the nutrients, compost quality, types of feedstocks and other factors. To evaluate the effects of compost application, it may involve a large number of parameter analyses, which can be costly and time ineffective. There is no indicator to reduce the number of analyses concerning the effect of compost application on soil fertility. In this study, a ranking method is proposed to identify the minimum number of parameters able to track the effect of compost application on soil fertility and the environmental impact. A total of 23 soil parameters were selected through literature review and ranked for their importance to show the effect of compost use. The ranking method was developed based on (1) the reporting frequency of environmental and soil fertility parameters and (2) impact of the selective parameter to the environment. Soil C and N contents were found to be the most frequently reported parameters (85 and 90 %) to affect soil fertility upon compost application. Both contents in the soil also change significantly before and after compost application. Heavy metals and N2O emissions were found to impact the environment most due to the toxicity of heavy metal to the environment and human health and high global warming potential of N2O. Based on the ranking method, nine parameters (N, NO3--N, P, K, micro-nutrients, heavy metals, C, pH and N2O emissions) were selected. 60 % of soil analyses were reduced following this ranking method. For the future study, a weightage system could be implemented on each criterion to decide the more essential parameters to be evaluated based on different soil or crop type and under different agricultural practices.