Aims: The study aims to analyze the genetic variability in diverse rice genotypes and establish correlations with grain yield and its attributes. By identifying and quantifying the genetic elements influencing grain yield and associated traits, the research intends to offer insights for developing high-yielding and resilient rice varieties, ultimately enhancing food security and agricultural sustainability. Study Design: The experiment was set up in a randomized complete block design (RCBD) with two replications, using a spacing of 20 cm × 15 cm. Place and Duration of Study: The experiment was conducted at the Instructional Farm of Uttar Banga Krishi Viswavidyalaya, Pundibari, Cooch Behar, West Bengal during the Kharif season (the period from June to October) of 2019 and 2020. The duration of the study encompassed the entire Kharif seasons of both years. Methodology: The study evaluated forty-two diverse rice genotypes based on nine agro-morphological traits. The methodology encompassed the utilization of ANOVA to evaluate significant differences in trait means and discern genetic variability among rice genotypes. Central tendency and variability were assessed through the calculation of mean, range, and standard deviation to gain insights into genetic variation. Furthermore, variation among traits was quantified using phenotypic and genotypic coefficient of variation to aid in understanding genetic variability. Heritability in broad sense was estimated to ascertain the genetic contribution to the observed variation, while the identification of traits with potential for improvement was achieved through the analysis of genetic advance as percent of mean. Furthermore, correlation and path coefficient analyses were conducted to comprehend the connections between the agro-morphological traits and grain yield, offering insights into the genetic relationships among the traits and their direct and indirect impacts on grain yield patterns. Results: The analysis of variance results confirmed the presence of significant differences among the evaluated genotypes. The phenotypic coefficient of variation displayed elevated values, closely associated with the genotypic coefficient of variation for all traits. Both phenotypic and genotypic coefficient of variation values were observed to be low to moderate for all the nine traits. Furthermore, specific traits such as grain breadth, panicles plant-1, and grain L/B ratio exhibited high heritability and high genetic advance percentage of mean, indicating their potential for selection and improvement in breeding programs. Additionally, the correlation study at the genotypic level revealed positive and significant correlations between grain yield plant-1, test weight, and spikelet fertility. Moreover, the path coefficient analysis showed that grain length had the maximum positive direct effect on grain yield plant-1. Conclusion: In conclusion, the analysis revealed significant genotype variations across multiple traits, indicating potential for targeted breeding improvements. Traits like grain breadth, panicles plant-1, and grain L/B ratio showed promising heritability and genetic advancement, emphasizing their value for selection in breeding programs. Correlation and path coefficient analyses highlighted interrelationships and direct effects on yield, underlining the importance of genetic factors in trait expression.