## 1 Introduction  
Encapsulation is widely used in numerous industries, including food, cosmetics, biology, agriculture, and pharmacy [1; 2; 3]. The nature of the encapsulation technique involves stabilizing active compounds using building systems to preserve their physical, chemical, and biological properties under various conditions. There are two main kinds of encapsulation techniques: physical and chemical. The first uses techniques that influence intensive properties, such as temperature and pressure [3], whereas the second, chemical encapsulation, leverages the active compounds' chemical properties [4]. Due to the method's complexity, significant obstacles exist [5] despite the technique's extensive range of applications. One of these obstacles is the compatibility between the active compound and the shell material (encapsulant compound) [6; 7]. Among the widespread use of the technique and the varying amounts of compounds, antioxidant compounds (ACs) are significant for their properties in the abovementioned industries. Antioxidants include polyphenols, carotenoids, anthocyanins, catechins, vitamins, and polyunsaturated fatty acids. They can be found in fruits, vegetables, cereals, and plants [8; 9]. These compounds serve multiple functions. Plants, for example, offer structural support and defense against environmental factors such as biotic and abiotic stress,ultraviolet radiation, and pathogens. On the other hand, consumers benefit from these compounds' properties, which protect against noncommunicable diseases (NCDs) by acting as regulators of cellular processes such as enzyme inhibition, gene expression, and protein phosphorylation. These compounds affect the sensory qualities of fruits and vegetables, such as bitterness, color, and flavor, resulting in a unique sensory profile for each product based on the compound present [10]. Due to their capabilities, the bioactive compounds mentioned above can be utilized in various industries. Nevertheless, these compounds' capacity is constrained by various obstacles that must be overcome. Nowadays, the bioavailability, bioavailability, and bioactivity of antioxidant compounds are issues due to negative extrinsic factors such as poor stability of compounds in various mediums [11], lack of transportation vehicles, and challenging absorption [12]. Subsequently, encapsulation could solve these concerns, promote stability, and pursue maintenance or increase the stated capabilities [13]. Compatibility between the active and encapsulant compounds (WM) is crucial in encapsulation. This relevance is due to the affinity between the compounds, influenced by various chemical properties. Most of the time, suitable matches are complex, requiring costly and time-consuming trial-and-error experiments [6]. To bridge this gap, the design and implementation of a computational tool could support decision-making processes regarding the time and resources required for this purpose in experimental development [14]. Various tools could be proposed in this regard; however, there have been remarkable advancements in machine learning (ML) for classification problems in recent years. Several research studies have considered machine learning (ML) to address the issues of determining compatibility between substances. [PERSON] et al. suggested utilizing artificial intelligence (AI) and machine learning (ML) to facilitate drug development and identify protein-protein interactions and drug target interactions [15]. [PERSON] et al. examined the application of Deep Learning (DL) in several cheminformatics methodologies for predicting the binding affinity between chemicals and proteins, focusing on the drug-target interaction. [PERSON] et al. used an unambiguous multiple linear regression (MLR) algorithm to build QSAR models of the estrogen receptor binding affinity [16]. [PERSON] et al. used a Support Vector Machine (SVM) regression with bootstrapping for creating and validating QSAR models to examine the DNA-binding characteristics of a library of aminoglycos-polyamine compounds [17].