Fractional　flow　reserve　(FFR)　is　the　＂gold　standard＂　for　diagnosis　of　myocardial　ischemia.　The　existing　3D　computational　fluid　dynamics　(CFD)　algorithm　based　on　coronary　computed　tomography　angiography　(CTA)　has　realized　the　non-invasive　calculation　of　FFR　(FFRCT),　but　the　CFD　simulation　in　3D　coronary　arteries　is　time　consuming.　The　purpose　of　this　study　was　to　develop　a　reduced-order　(0D)　cardiovascular　model　for　rapid　computation　of　pressure　and　flow　through　coronary　arteries　and　stenosis　and　to　ensure　accuracy　in　prediction　of　FFR　(FFR0D).　One　hundred　patients　(118　lesions)　who　had　undergone　invasive　FFR　were　enrolled　retrospectively.　Based　on　coronary　CTA,　a　patient-specific　lumped　parameter　model　of　the　cardiovascular　system　and　coronary　system　was　constructed.　In　addition,　an　experimentally　validated,　theoretical　calculation　model　of　stenosis　resistance　was　introduced.　Stenosis　resistance　and　flow　rate　were　quantified　by　coupling　the　two　models,　and　FFR0D　was　calculated　according　to　the　coronary　pressure　distribution.　The　overall　modeling　time　of　FFR0D　was　approximately　41.2　min　while　FFRCT　was　reported　to　be　3.5　h.　Using　the　clinical　cut-off　value　of　FFR　(0.8),　the　accuracy,　sensitivity,　specificity,　positive　predictive　value　and　negative　predictive　value　of　FFR0D　were　89.8%,　79.2%,　92.6%,　73.1%　and　94.6%,　respectively,　while　that　of　FFRCT　were　reported　to　be　84.3%,　87.9%,　82.2%,　73.9%　and　92.2%,　respectively.　We　successfully　proposed　a　reduced-order　cardiovascular　model　for　rapid　and　accurate　prediction　of　FFR.　Compared　with　FFRCT,　FFR0D　reduced　computational　cost　and　ensured　computational　accuracy　in　the　case　of　our　limited　samples.　These　advantages　represent　an　advance　in　the　diagnosis　and　treatment　of　myocardial　ischemia.(c)　2022　Elsevier　B.V.　All　rights　reserved.