Currently bioinformatics and artificial intelligence (AI) can assist in the development and application of bioremediation, as microorganisms display a wide range of contaminant degradation abilities that can efficiently and effectively bring back natural environmental conditions. With the availability of many types of AI algorithms, it has become familiar for researchers to apply the off-shelf systems to classify and mine their database. AI offers an advanced toolbox that better facilitates problem-solving in the field. The current trends in AI are; machine learning methods which help creating more efficient, reliable, accurate neural networks and tools for determining natural and xenobiotic compounds’ structures and biodegradative pathways. This chapter aims to illustrate the relation between bioremediation and bioinformatics through machine learning models that would introduce bioremediation as a predictive tool.