Agriculture　is　increasingly　facing　major　challenges　such　as　climate　change,　scarcity　of　natural　resources,　and　changing　societal　demands.　To　tackle　these　challenges,　there　is　a　pressing　need　to　evolve　towards　more　sustainable　agricultural　practices.　As　a　result,　sustainability　stands　among　the　most　relevant　topics　in　agricultural　research　worldwide,　and　countries　along　the　Belt　and　Road　(B&R)　route　are　no　exception.　This　paper　selected　25　indicators　from　the　five　subsystems　of　population,　society,　economy,　environment,　and　resources　in　order　to　build　an　evaluation　index　system　of　agricultural　sustainable　development　capability,　and　then　it　used　an　improved　entropy　weight　method,　technique　for　ordering　preference　by　similarity　to　an　ideal　solution　(TOPSIS),　and　coordination　degree　method　to　measure　the　comprehensive　capability　and　coordination　of　agricultural　sustainable　development　of　all　countries　along　the　B&R　route　from　2006　to　2015.　First,　according　to　the　time　dimension,　the　comprehensive　score　of　sustainable　development　capability　of　agriculture　along　the　B&R　route:　This　had　an　average　annual　score　of　0.3195　which　initially　decreased,　then　increased　in　a　fluctuating　manner,　before　finally　falling　again.　Second,　according　to　the　spatial　dimension,　the　average　comprehensive　score　of　agricultural　sustainable　development　capability　showed　an　evolutionary　trend　of　high-low-high-low-high＇　from　west　to　east,　which　showed　an　obvious　basic　spatial　pattern　of　the　W＇　type.　Third,　from　the　perspective　of　the　subsystems　of　agriculture,　although　the　coordination　degree　among　subsystems　in　the　main　grain-producing　areas　increased　continually　from　2006　to　2015,　the　overall　level　of　development　needed　to　be　further　improved.　In　order　to　further　clarify　the　main　factors　affecting　the　capability　of　agricultural　sustainable　development,　this　paper　selected　six　explanatory　variables:　The　level　of　economic　development,　financial　expenditure　for　agriculture,　agricultural　foreign　direct　investment,　agricultural　labor　force,　the　intensity　of　agricultural　R&D　investment,　and　the　level　of　agricultural　informatization.　Then,　geographically　and　temporally　weighted　regression　was　applied　to　evaluate　the　direction　and　degree　of　influences　of　selected　factors　on　sustainability　development　capability　of　agriculture.　The　results　showed　that　the　regression　coefficients　of　each　variable　in　53　countries　were　positive　or　negative,　which　indicated　that　the　influencing　factors　of　agricultural　sustainable　development　capacity　had　the　characteristics　of　geospatial　nonstationarity.