Macroalgae are a great source of antioxidants, which show valuable pharmacological properties and benefit human health [1]. The growing interest in marine algae is driven by their plentiful natural bioactive compounds, with biological benefits such as antioxidative, anti-inflammatory, antimicrobial, anticancer, and cardioprotective properties [2], which hold promise for the food and pharmaceutical industries [3,4]. The macroalgae species Fucus vesiculosus, Asparagopsis armata, Saccorhiza polyschides, and Stigeoclonium subsecundum were studied. The F. vesiculosus species represents a rich source of compounds such as polyphenols, and one particular group of polyphenols found in these brown algae are phlorotannins, which have a wide range of biological activities such as antibacterial, antioxidant, anti-tumor, anti-inflammatory, and anti-allergic activities [5]. The extracts were evaluated concerning their antioxidant activity, phenol concentration and antimicrobial activity. The results of the total phenol and antioxidant assays showed that Fucus vesiculosus extracted with acetone and water had the highest content of both total phenols and antioxidants. Additionally, we also evaluated how the Fourier Transform Infrared Spectroscopy (FTIR) spectra of the extracts could be correlated with their antioxidant properties. The results of FTIR showed that some of the species at specific concentrations had very similar chemistry properties after the analysis of their spectra, with the results of Partial Least Squares (PLS) indicating good correlation between the solvent and extract variables. Based on different solvents, it is possible to improve the extraction of the most suitable antioxidant compounds and consequently to develop a faster and more efficient model for analyzing their respective biomolecular effects, as well as classification models associated with machine learning techniques to save time and resources.