Quantitative traits are measurable phenotypic traits influenced by the combined effects of multiple genes and environments, leading to phenotypic variation among individuals. Linking phenotypes and genotypes using statistical techniques to underline the genetic factors that regulate the quantitative variation of complex traits with agricultural and evolutionary significance is crucial to crop improvement for plant breeders. Most of the agronomically important traits show quantitative inheritance, which is regulated by quantitative trait loci (QTL), environment, and the interaction between environmental factors and QTL. At present, QTL mapping and association mapping are the two most frequently utilized tools for interpreting the relationship between genes and complex traits. Both techniques emerge as an indispensable tool in the breeder’s toolkit, a beacon of hope in the quest to developing resilient, high-yielding, and quality crop varieties capable of sustaining the growing global population. Successful QTL and association mapping rely on the precision of marker-trait association, which largely depends on the marker density, its quality, and accuracy in the phenotypic data. Recent advancements in genomic technology and the development of robust statistical analysis methods have made QTL and association mapping an attractive and cost-effective approach for plant research programs. Increased marker density supplemented with accurate and precise phenotyping using high-throughput tools and techniques improves the power of QTL and significant marker identification. This chapter gives an overview of the various tools and techniques used in QTL and association mapping studies. We have discussed comprehensive details on the development of various mapping populations, recent tools and techniques for high-throughput phenotyping and genotyping, and different statistical methods and software employed in molecular plant breeding research.