A refrigerant amount inference apparatus that infers a refrigerant amount in an air conditioner in which a compressor, a heat source side heat exchanger, a supercooling heat exchanger, a pressure reducing valve, and a use side heat exchanger are connected to piping, the supercooling heat exchanger being a heat exchanger that exchanges heat between refrigerant that passes through a supercooling bypass expansion valve provided in a bypass circuit and refrigerant in a mainstream circuit, the bypass circuit being connected to piping on a suction side of the compressor from a position between the heat source side heat exchanger and the supercooling heat exchanger or from a position between the pressure reducing valve and the supercooling heat exchanger, the refrigerant amount inference apparatus comprising: a training data storage unit storing training data, and a refrigerant amount inference unit configured to acquire a state of refrigerant in first piping provided between the pressure reducing valve and the supercooling heat exchanger with a supercooling degree acquiring unit and data from the training data storage unit, and an operation amount related to the state of the refrigerant in the first piping and including a degree of an opening of the supercooling bypass expansion valve with an expansion valve opening acquiring unit and data from the training data storage unit wherein the refrigerant amount inference unit performs machine learning to generate a refrigerant amount inference model by using the state of the refrigerant in the first piping, the operation amount related to the state of the refrigerant in the first piping, and the refrigerant amount as the training data, so that the refrigerant amount inference model outputs the refrigerant amount in response to the state of the refrigerant in the first piping and the operation amount related to the state of the refrigerant in the first piping being input into the refrigerant amount inference model. in which a compressor, a heat source side heat exchanger, a supercooling heat exchanger, a pressure reducing valve, and a use side heat exchanger are connected to piping, the supercooling heat exchanger being a heat exchanger that exchanges heat between refrigerant that passes through a supercooling bypass expansion valve provided in a bypass circuit and refrigerant in a mainstream circuit, the bypass circuit being connected to piping on a suction side of the compressor from a position between the heat source side heat exchanger and the supercooling heat exchanger or from a position between the pressure reducing valve and the supercooling heat exchanger, the refrigerant amount inference apparatus comprising: a training data storage unit storing training data, and a refrigerant amount inference unit configured to acquire a state of refrigerant in first piping provided between the pressure reducing valve and the supercooling heat exchanger with a supercooling degree acquiring unit and data from the training data storage unit, and an operation amount related to the state of the refrigerant in the first piping and including a degree of an opening of the supercooling bypass expansion valve with an expansion valve opening acquiring unit and data from the training data storage unit wherein the refrigerant amount inference unit performs machine learning to generate a refrigerant amount inference model by using the state of the refrigerant in the first piping, the operation amount related to the state of the refrigerant in the first piping, and the refrigerant amount as the training data, so that the refrigerant amount inference model outputs the refrigerant amount in response to the state of the refrigerant in the first piping and the operation amount related to the state of the refrigerant in the first piping being input into the refrigerant amount inference model. a training data storage unit storing training data, and a refrigerant amount inference unit configured to acquire a state of refrigerant in first piping provided between the pressure reducing valve and the supercooling heat exchanger with a supercooling degree acquiring unit and data from the training data storage unit, and an operation amount related to the state of the refrigerant in the first piping and including a degree of an opening of the supercooling bypass expansion valve with an expansion valve opening acquiring unit and data from the training data storage unit wherein the refrigerant amount inference unit performs machine learning to generate a refrigerant amount inference model by using the state of the refrigerant in the first piping, the operation amount related to the state of the refrigerant in the first piping, and the refrigerant amount as the training data, so that the refrigerant amount inference model outputs the refrigerant amount in response to the state of the refrigerant in the first piping and the operation amount related to the state of the refrigerant in the first piping being input into the refrigerant amount inference model.