Background/Context: In order to stimulate national and regional economic growth, policymakers and businesses have expressed great interest in growing the supply of workers with skills in science, technology, engineering, and math (STEM). At the same time, considerable efforts are being devoted to narrowing race and gender gaps in the STEM training pipeline. A key link in this pipeline is high school, where learning experience plays a critical role in shaping student's interest in STEM careers (e.g., Bottia et al, 2015; Corin, et al 2020). This is also the period when females begin to lose interest in STEM (Sadler, et al., 2012). To improve STEM education, one of the national initiatives during the early 2010's focused on integrated applied STEM curricula (Gottfried & Bozick, 2016). By connecting the traditional STEM disciplines to the real-world/applied problems, the goal was to increase student participation in more meaningful and engaging STEM learning and generate greater interest in STEM or related careers. Project Lead the Way (PLTW) is one such program. PLTW began over two decades ago in a handful of high schools as career and technical education (CTE). Since then program has grown rapidly and is currently adopted by over 12,000 high schools nationally. In Missouri, the site of this study, the program expanded from 13 schools in 2005 to 174 schools by 2020--roughly 35% of all public high schools. Purpose/Objective/Research Question: Rigorous empirical evidence on applied STEM program is limited. This study investigates the impact of PLTW program offering (ITT) and the participation impact on participants (TOT). The outcomes include college enrollment, STEM major declaration, overall degree attainment, and STEM degree attainment. Setting: Missouri has 537 traditional and charter public high schools, and 26% of them are in urban and suburban areas, and 18% and 57% are in town and rural areas, respectively. Population/Participants/Subjects: We use three cohorts of first-time 9th-grade students who began high school in AY2010, AY2013, and AY2014 (N? 68,000 per cohort). Racial compositions are 75.8% White, 16.5% Black, 4.2% Hispanic, and 3.6% others. The FRL rate is 42.4%. The analytic population consists of students in two types of schools: schools that began offering PLTW for the 2013 and/or 2014 cohorts, but not for the 2010 cohort (N=92 schools and 43,578 students) and schools that never offered PLTW for the three cohorts (N=273 schools and 49,788 students). The two types of schools are academically similar, but they differ considerably in demographic characteristics: PLTW schools are larger in size; are located in urban and suburban areas; have larger Black or Hispanic student populations; and have lower FRL rates than non-PLTW schools (Table 1). Intervention/Program/Practice: PLTW is designed to provide active, project-based learning in the largest three applied STEM fields--Engineering, Computer Science, and Biomedical Science ("Pathways"). Each pathway begins with foundational courses. They provide an overview and introduce major ideas of the field with a goal of developing an enthusiasm for further study. Advanced courses are designed to expand students' understanding of the field through deeper and specialized content. The Engineering and Biomedical Science pathways end with a capstone course which requires students to take their own idea from design through development of a product or plans to produce one. Research Design: First, we apply a Difference-in-Differences analysis (DiD) to estimate the impact of program offering for PLTW schools. This is estimated by deciles of "prognostic scores"--predicted probability of completing a STEM degree given pre-treatment predictors (math and science test scores and GPAs) . Students in non-PLTW schools serve as a comparison group, providing an estimate of the outcome difference between the 2010 and later cohorts in the absence of PLTW. Next, the propensity-score adjusted DiD is used to estimate the impact of program participation on participants (TOT). Propensity scores--the probability of program participation given pre-treatment covariates-- are used to construct the "would be treated" and "would be untreated" populations from the 2010 cohort who are made similar to, respectively, the 2013/2014 program participants and non-participants in the same PLTW school. The would-be-untreated and observed-untreated students and students in non-PLTW schools are two comparison groups for the DiD analysis. In additional DiD analysis, these two comparison groups are weighted/matched to resemble the program participants. Data Collection and Analysis: Student data are provided by Missouri Department of Elementary and Secondary Education. The K-12 data are linked to National Student Clearinghouse data for post-secondary outcomes. The ITT impact for student i, cohort c, and school j is estimated as; Y_icj=d_ij+ [beta]eta_cd(d_ij*PLTW_j*Coh_c)+G(X_ij)+ Coh_c*d_ij+ S_j+ e_ij, where dij are indicators for prognostic-score deciles; PLTW distinguishes PLTW and non-PLTW schools; X is student covariates; Coh_c is cohort indicators; s_j is school fixed effects. The coefficients, [beta]_c_d, indicate the cohort- and decile-specific ITT impact. The ITT analysis avoids selection bias around program participation, but estimates may be small due to low participation rates, especially for the 2013 cohort (Table 2). The model for TOT impact is; Y_icj=a0+ a1(Untreat_coh10,ij) + a2 (Treat_coh10,ij))+ a3(Coh_c )+ a4(Coh_c*Untreat_ij ) + delta(Coh_c*Treat_ij)+a5(X_ij)+ e_ij,, Where a0 is the average outcome for the 2010 students in non-PLTW schools; Untreated_coh10 and Treated_coh10 are, respectively, the PS-matched/weighted "would be untreated" and "would be treated" 2010 students in the PLTW school. The program impact is given by delta. Note that a_3=a_4 under the paralell trends assumption. Results: First, Table3 presents base-line outcomes. Table 4 shows positive ITT effects on STEM major declaration and STEM degree completion for the top deciles. Program participants also had higher STEM enrollment and degree completion (Tables 5 and 6). Conclusions: Our evidence suggests that an applied STEM program like PLTW has a potential to increase post-secondary TEM outcomes among students with higher STEM readiness. The study's limitations include bias due to unobserved confounders. We will conduct sensitivity analyses to address this issue.