In　engineering　structures　that　are　subject　to　cyclic　loading,　monitoring　and　assessing　fatigue　crack　growth　(FCG)　plays　a　crucial　role　in　ensuring　reliability.　In　this　study,　the　acoustic　emission　(AE)　technique　was　used　to　monitor　the　FCG　behavior　of　2.25Cr1Mo0.25V　steel　in　real-time.　Specifically,　an　AE　multi-parameter　analysis　was　conducted　to　qualitatively　assess　the　crack　growth　condition　and　quantitatively　correlate　the　crack　growth　rate　with　AE.　Various　AE　parameters　were　extracted　from　AE　signals,　and　the　performances　of　different　AE　parameters　were　analyzed　and　discussed.　The　results　demonstrated　that　four　stages　of　FCG,　which　correspond　to　macrocrack　initiation,　stable　crack　growth　with　low　crack　growth　rate,　stable　crack　growth　with　high　crack　growth　rate,　and　unstable　crack　growth,　are　distinctly　identified　by　several　AE　time　domain　parameters.　The　sudden　and　continuous　occurrence　of　many　AE　signals　with　high　count　(＞100)　and　high　energy　(＞40　mV　center　dot　ms)　can　provide　early　and　effective　warning　signs　for　accelerated　crack　growth　before　final　failure　occurs.　Moreover,　linear　correlations　between　crack　growth　rate　and　different　AE　parameters　are　established　for　quantifying　crack　growth.　Based　on　the　AE　multi-parameter　analysis,　it　was　found　that　the　count,　energy,　and　kurtosis　are　superior　AE　parameters　for　both　qualitatively　and　quantitatively　characterizing　the　FCG　in　2.25Cr1Mo0.25V　steel.　Results　from　this　research　provide　an　AE　strategy　based　on　multi-parameter　analysis　for　effective　monitoring　and　assessment　of　FCG　in　engineering　materials.