The estrogen receptor gene (ESR1) is expressed in approximately two-thirds of breast cancers (BCs) and predicts sensitivity to endocrine therapy. Mutations in ESR1 have recently been associated with endocrine therapy resistance in patients with estrogen receptor positive metastatic breast cancer (ER+ MBC). Thus, monitoring the status of ESR1 mutations may facilitate personalized therapy decisions for ER+ MBC patients. Additionally, mutations in PIK3CA and TP53 are also prevalent in ER+ MBC and may influence therapeutic responses. Recent studies demonstrate mutational heterogeneity in metastatic breast cancer (MBC), highlighting a need to monitor for the emergence of new mutations over time. The analysis of blood plasma circulating tumor DNA (ctDNA) by next generation sequencing (NGS) has emerged as an attractive approach to address the mutation heterogeneity and evolution of MBC over time. However, the high costs and intensive bioinformatics required for plasma ctDNA NGS analysis limit its utility in clinical studies that require longitudinal monitoring. We have recently developed and validated an assay for plasma ctDNA mutation profiling that utilizes droplet PCR-based multiplexed target enrichment followed by NGS, which we have termed dPCR-Seq. Here we describe the protocol for dPCR-Seq, illustrating its relative simplicity in library preparation and bioinformatics analysis to detect ESR1 (all coding regions), TP53 (all coding regions), PIK3CA (hotspots), PIK3R1 (hotspots), and POLE (exonuclease domain) mutations in breast cancer patients. We have validated a subset of the ESR1 mutations identified by dPCR-Seq using allele-specific digital PCR (dPCR) assays, demonstrating exceptional concordance in the measurement of mutant allele frequency (MAF) in clinical plasma ctDNA specimens. We anticipate that dPCR-Seq may have practical utility in future studies that investigate longitudinal monitoring of plasma ctDNA mutations as potential biomarkers of therapeutic response in ER+ MBC patients.