About 48.5 million couples i.e., one in four couples experience infertility worldwide, which is notably prevalent in India. This study investigates the multifaceted relationships between metabolic diseases like hyperthyroidism, diabetes type 2, recurrent implantation failure (RIF) and reproductive health. Understanding that these disorders have genetic roots, we used co-expression analysis to discover significant genes and pathways associated with reproductive health. This gives us novel insight into the molecular cause of infertility. We systematically processed and examined the pattern of gene expression for hyperthyroidism (GSE178996), RIF (GSE26168) and diabetes (GSE16532) using a publicly available database from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO). In each type of disease, differential expression analysis found several genes that were both up-regulated and down-regulated genes. To understand the differences and similarities between these diseases, co-expression networks were built, with a focus on identifying key hub genes crucial in controlling diseases. Our research analysed probable disease-associated genes ABCC6 and SLC2A14 and elucidated their functions in diseases. GO analysis, revealed enriched biological pathways and processes important for reproductive health. Lastly, we used the Feed-Forward Neural Network (FFNN) model with dropout and L2 regularization for text clarification, which distinguished between the investigated conditions with an overall accuracy of 96.43%. In conclusion, the complex landscape of genes connected to reproductive health and their relationship with diseases are revealed by this thorough study. These results create the basis for more investigation that could lead to reproductive health-related therapeutics and diagnostic approaches.