<p>The environmental impact assessment is substantial in protecting the environment and preserving natural resources. While describing the environmental impact characterizations by use of objective indicators mean values is frequently not possible, there is a high degree of uncertainty associated with the estimation caused by the different criteria and judgments on values. Therefore, for conveying these values to a mathematical form and vice versa short of losing the meaning of information is an essential step to solve the problem of assigning membership and non-membership degrees of an object to a set by decision-makers. This kind of information has built-in suitable uncertainty sets called bipolar complex intuitionistic fuzzy sets (BCIFS) by extending the range of membership and non-membership degrees in BIFS from [− 1, 1] to unit squares in the complex plane. In this research, a BCIFS has been generalized to represent the magnitude and impact indicators in the EIA. Therefore, the formal definition of BCIFS is introduced as its ability to employ both real and imaginary parts for bipolar intuitionistic fuzzy information representation, and some basic operations on BCIFS have also been presented. This study presents a decision-making algorithm and real-life applications to display the success and usability of BCIFS in environmental impact evaluation.</p>