Reliability analysis methods are used to evaluate the safety of reinforced concrete structures by evaluating the limit state function 𝑔(𝑋𝑖). For implicit limit state function and nonlinear analysis , an advanced reliability analysis methods are needed. Monte Carlo simulation (MCS) can be used in this case however, as the number of input variables increases, the time required for MCS also increases, making it a time consuming method especially for complex problems with implicit performance functions. In such cases, MCS-based FORM (First Order Reliability Method) and Artificial Neural Network-based FORM (ANN FORM) have been proposed as alternatives. However, it is important to note that both MCS-FORM and ANN-FORM can also be time-consuming methods in their own right. MCS-FORM involves running multiple MCS, and the time required increases with problem complexity and desired precision. ANN-FORM, on the other hand, can be faster for repetitive reliability assessments, but the training phase can be computationally expensive, and accuracy depends on training data quality and quantity. To address this computational challenge and enhance the efficiency of reliability analysis, a novel method is proposed in this paper. This method leverages the capabilities of ABAQUS, in combination with MATLAB. The key objective of this proposed approach is to automate and streamline the repetitive tasks involved in reliability analysis, thereby significantly reducing the computational time required for such analyses. The method is based on the development of a custom ABAQUS Python script file, which interfaces with MATLAB. The script serves as a bridge between the finite element analysis capabilities of ABAQUS and the data processing and analysis capabilities of MATLAB. An illustrative example was considered to demonstrate the application of the proposed method. In this example, a deteriorated simply supported concrete beam with an implicit performance function was analysed. The objective was to assess the reliability of the beam under the given conditions. To perform this reliability analysis, the two methods were employed: MCS-FORM and ANN-FORM. Both of these methods were implemented in conjunction with the newly developed approach that integrates ABAQUS and MATLAB. The results of this analysis were quite promising. Both MCS-FORM and ANN-FORM successfully estimated the reliability of the concrete beam, and they exhibited a high level of agreement in their assessments. This presented method demonstrates its suitability for the application of reliability analysis in scenarios such as the one presented. Its efficiency in automating repetitive tasks not only simplifies the analysis process but also facilitates the generation of multiple simulations. By doing so, it significantly minimizes the time and computational resources required for reliability assessments.