Molecular imprinting is one of the promising techniques that have been used recently to detect trace contaminants in aqueous solution. This technique is based on the fact that the target compound is present during the polymer synthesis which gives an opportunity for the molecularly imprinted polymers (MIP) to rebind the target molecule selectivity after removal. In this thesis, it was used to detect a hormone (testosterone) in water and blood samples. The procedures are straightforward, fast, and use simple equipment. The detection of the template was carried out by using HPLC and UV-Vis. The MIP starts by preparing a template for the polymer morphology from a silica particle deposition on the glasses slides. At the beginning of this research, the silica particles were prepared by using the Stober method and then commercial silica particles were used. Bulk polymerization was used to prepare the polymer. Two types of solvent (porogen) have been applied. The composition of the prepolymerization solution was optimized. The smart sensor was used first as a self-standing film to characterize and validate. After that, the sensor was deposited on a Poly (methyl methacrylate) (PMMA) slide as a support material which made it easy to use and regenerate. The selectivity and sensitivity of the sensor to the target (testosterone) were studied. The sensor has the potential to detect testosterone not only in a water sample but also in blood samples. In addition, this sensor has the potential for integration into a microdevice for on-site and online monitoring. Such a sensor could be easily used by an inexperienced operator. In this work, the sensor was developed to detect the target with a very low concentration in blood samples. Different endocrine disrupted chemicals were used to compete for the target and to test the potential interference effect. Several human blood samples were utilized to investigate the sensor selectivity. Also, the recoverability of the sensors was studied. The detection of endocrine-disrupting chemicals by traditional methods was complicated, expensive and time-consuming. This research studied the affinity of eight EDCs to the testosterone sensor. In addition, the relation between the classification of chemicals depend on relative binding affinity (RBA) which calculated from other sources to the classification that were got from the sensor were compared to investigate any relationship between. Based on the results of the study, the chemicals were classified into 4 categories, according to their response: strong affinity (T), moderate (CHL, VIN, EST, and FLU), weak (BPA, DDE, and DCP), and inactive (DDT). Also, the percent activity showed that the selected chemicals had lower adsorption to the binding site of the sensor in comparison with testosterone. The results showed that 57 [percent] of our classification was identical with Fang classification which means that our sensor can be used as a pre method to study the affinity of EDCs binding to AR.